{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 熊猫(pandas)简介\n",
    "* 来源: [官方英文新手教程](https://pandas.pydata.org/pandas-docs/version/1.0.2/getting_started/index.html#getting-started)\n",
    "* 课堂教学方式：\n",
    "   * 分段式以英文新手教程的内容做示范及说明\n",
    "   * 课堂上以实际中文数据做操练，每段约10-15分钟\n",
    "   * 抽学生联mic自播说明难点及成果点，教师总结\n",
    "* 关於新旧内容\n",
    "   * 旧Python内容若有不熟处，会按课堂教学实际状况记录后，在往后的课程补充\n",
    "   * 新Pandas内容请大家以下操演的心法及剑法学习\n",
    "       * **将代码当成人类语言**用**片语化**记忆，并配合\n",
    "       * **将数据处理输入输出**用**视觉语言**记忆\n",
    "       \n",
    "![02_io_readwrite](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/02_io_readwrite.svg)\n",
    "\n",
    "* 以上为官方英文新手教程例子，数据处理\n",
    "  * 输入有  **read_叉叉**  方法  \n",
    "  * 输出有  **to_叉叉**  方法  \n",
    "  * 可配合多种数据做输入输出\n",
    "  * 片语法记忆：以常用之csv及xlsx输入输出为例\n",
    "     * 数据框.read_csv( 档名, 参数 ... )\n",
    "     * 数据框.read_excel( 档名, 参数 ... )\n",
    "     * 数据框.to_csv( 档名, 参数 ... )\n",
    "     * 数据框.to_excel( 档名, 参数 ... )\n",
    "  * 人类语言片语化，可组合\n",
    "     * 输入 数据框.read_支援的格式名\n",
    "     * 输出 数据框.to_支援的格式名\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "/* 本电子讲义使用之CSS */\n",
       "div.code_cell {\n",
       "    background-color: #e5f1fe;\n",
       "}\n",
       "div.cell.selected {\n",
       "    background-color: #effee2;\n",
       "    font-size: 2rem;\n",
       "    line-height: 2.4rem;\n",
       "}\n",
       "div.cell.selected .rendered_html table {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html pre code {\n",
       "    background-color: #C4E4ff;   \n",
       "    padding: 2px 25px;\n",
       "}\n",
       ".rendered_html pre {\n",
       "    background-color: #99c9ff;\n",
       "}\n",
       "div.code_cell .CodeMirror {\n",
       "    font-size: 2rem !important;\n",
       "    line-height: 2.4rem !important;\n",
       "}\n",
       ".rendered_html img, .rendered_html svg {\n",
       "    max-width: 45%;\n",
       "    height: auto;\n",
       "    float: right;\n",
       "}\n",
       "/* Gradient transparent - color - transparent */\n",
       "hr {\n",
       "    border: 0;\n",
       "    border-bottom: 1px dashed #ccc;\n",
       "}\n",
       ".emoticon{\n",
       "    font-size: 5rem;\n",
       "    line-height: 4.4rem;\n",
       "    text-align: center;\n",
       "    vertical-align: middle;\n",
       "}\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<style>\n",
    "/* 本电子讲义使用之CSS */\n",
    "div.code_cell {\n",
    "    background-color: #e5f1fe;\n",
    "}\n",
    "div.cell.selected {\n",
    "    background-color: #effee2;\n",
    "    font-size: 2rem;\n",
    "    line-height: 2.4rem;\n",
    "}\n",
    "div.cell.selected .rendered_html table {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html pre code {\n",
    "    background-color: #C4E4ff;   \n",
    "    padding: 2px 25px;\n",
    "}\n",
    ".rendered_html pre {\n",
    "    background-color: #99c9ff;\n",
    "}\n",
    "div.code_cell .CodeMirror {\n",
    "    font-size: 2rem !important;\n",
    "    line-height: 2.4rem !important;\n",
    "}\n",
    ".rendered_html img, .rendered_html svg {\n",
    "    max-width: 45%;\n",
    "    height: auto;\n",
    "    float: right;\n",
    "}\n",
    "/* Gradient transparent - color - transparent */\n",
    "hr {\n",
    "    border: 0;\n",
    "    border-bottom: 1px dashed #ccc;\n",
    "}\n",
    ".emoticon{\n",
    "    font-size: 5rem;\n",
    "    line-height: 4.4rem;\n",
    "    text-align: center;\n",
    "    vertical-align: middle;\n",
    "}\n",
    "</style>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![01_table_dataframe.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/01_table_dataframe.svg)\n",
    "\n",
    "# 本周内容\n",
    "本周内容共分6段(5段+1段下周预告)，新手请认真记忆并操练，老手有彩蛋项目去实践\n",
    "\n",
    "* [熊猫处理什么样的数据？](#熊猫处理什么样的数据？)\n",
    "\n",
    "> <mark>框框框</mark>，探索，清理和处理数据在Pandas中，数据表称为DataFrame，数据科学家**变数variables**通常放(竖着的列)column，**观察observations**通常放(横着的行)row\n",
    "\n",
    "<br/><br/><br/>\n",
    "\n",
    "-----\n",
    "\n",
    "![02_io_readwrite.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/02_io_readwrite.svg)\n",
    "\n",
    "* [如何读写表格数据？](#如何读写表格数据？)\n",
    "\n",
    "> <mark>读读读，写写写</mark>，数据科学家不想浪费时间编程去处理不同数据格式，所以pandas集成了常用的现成的文件格式或数据源（csv，excel，sql，json，parquet等）...\n",
    "\n",
    "-----\n",
    "\n",
    "![03_subset_columns_rows.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/03_subset_columns_rows.svg)\n",
    "\n",
    "* [如何选择表格的子集？](#如何选择表格的子集？)\n",
    "\n",
    "> <mark>切切切</mark>，**切片** (英文叫slice) 是数据科学家找突破点的重要工具，是她们的数据解剖刀...\n",
    "\n",
    "-----\n",
    "\n",
    "![04_plot_overview.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/04_plot_overview.svg)\n",
    "\n",
    "* [如何在熊猫中绘图？](#如何在熊猫中绘图？)\n",
    "\n",
    "> <mark>绘绘绘</mark>，**绘图** ( 数据框.plot() ) 是数据科学家**以数据框为中心**的代码实践，减少以图表类型为开头的编程思维来作图\n",
    "\n",
    "-----\n",
    "\n",
    "![05_newcolumn_2.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/05_newcolumn_2.svg)\n",
    "\n",
    "* [如何从现有列创建派生新列？](#如何从现有列创建派生新列？)\n",
    "\n",
    "> <mark>列列列</mark>，派生新列意谓着变数variables的进一部转换，是数据科学家按步就班做ETL的过程，新派生列就是**变数variables**的转换\n",
    "\n",
    "-----\n",
    "\n",
    "![06_groupby.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/06_groupby.svg)\n",
    "\n",
    "* [如何计算汇总描述性统计信息？](#如何计算汇总描述性统计信息？)\n",
    "\n",
    "> <mark>算算算</mark>，描述性统计竟然代码可以这麽容易....，但难的仍是在数据科学家的数据定义及解释上\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![01_table_dataframe.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/01_table_dataframe.svg)\n",
    "## 熊猫处理什么样的数据？\n",
    "\n",
    "> <mark>框框框</mark>，探索，清理和处理数据在Pandas中，数据表称为DataFrame\n",
    "\n",
    "\n",
    "对数据科学家来说: \n",
    "\n",
    "* 竖着的列column通常放**变数variables**\n",
    "* 横着的行row通常放**观察observations**\n",
    "\n",
    "对数据及信息管理人员来说:\n",
    "* 表格数据（例如存储在电子表格或数据库中的数据）是很常见的，最主流的数据结构和查询语言是SQL\n",
    "* 树状文本数据（例如HTML, XML, JSON数据）是很常见的，HTML/XML最主流的查询语言是xpath\n",
    "\n",
    "<div class=\"emoticon\">🐷🙈🙉🙊🐷</div>\n",
    "\n",
    "<div class=\"emoticon\">🙈🐷🙉🐷🙊</div>\n",
    "\n",
    "<div class=\"emoticon\">🐷🙈🐷🙊🐷</div>\n",
    "\n",
    "----- \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 框框框的代码片语\n",
    "框框框的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "```python\n",
    "框框 = pd.DataFrame ( {\n",
    "        \"变数X\": [\"观察X1\", \"观察X2\", \"观察X3\", \"观察X4\"],\n",
    "        \"变数Y\": [\"观察Y1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数Z\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "      } )```\n",
    "\n",
    "记得，像人类语言一样，说的清楚，人就可以读的比较清楚....\n",
    "\n",
    "* pd.DataFrame 的主流参数是字典\n",
    "* 该字典的键keys是由变数构成，相当於表格中一行行的标题\n",
    "* 该字典的值values是由观察的列表构成，相当於表格中一行行的数据\n",
    "* 表格真的要是表格, 该字典的每个观察的列表数量必需齐一\n",
    "\n",
    "[小贴士] 最后一个逗点可有可无(为什麽?)，在pandas情境下最好留(为什麽?)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 框框框的课堂练习\n",
    "新手请认真记忆并操练 \n",
    "#### 练习A1-框框框的课堂建构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数X</th>\n",
       "      <th>变数Y</th>\n",
       "      <th>变数Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数X   变数Y   变数Z\n",
       "0  观察X1  观察Y1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "框框\n"
     ]
    }
   ],
   "source": [
    "# A1\n",
    "框框 = pd.DataFrame ( {\n",
    "        \"变数X\": [\"观察X1\", \"观察X2\", \"观察X3\", \"观察X4\"],\n",
    "        \"变数Y\": [\"观察Y1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数Z\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "      } )\n",
    "display (框框)\n",
    "print(\"框框\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数X</th>\n",
       "      <th>变数Y</th>\n",
       "      <th>变数Z</th>\n",
       "      <th>变数A</th>\n",
       "      <th>变数B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "      <td>观察Z1</td>\n",
       "      <td>观察Z1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数X   变数Y   变数Z   变数A   变数B\n",
       "0  观察X1  观察Y1  观察Z1  观察Z1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2  观察Y2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3  观察Y3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4  观察Y4  观察Z4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A1\n",
    "# 尝试更改\n",
    "框框 = pd.DataFrame ( {\n",
    "        \"变数X\": [\"观察X1\", \"观察X2\", \"观察X3\", \"观察X4\"],\n",
    "        \"变数Y\": [\"观察Y1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数Z\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "        \"变数A\": [\"观察Z1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数B\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "      } )\n",
    "display (框框)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数X</th>\n",
       "      <th>变数Y</th>\n",
       "      <th>变数Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数X   变数Y   变数Z\n",
       "0  观察X1  观察Y1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A1\n",
    "# 尝试更改\n",
    "框框 = pd.DataFrame ( {\n",
    "        \"变数X\": [\"观察X1\", \"观察X2\", \"观察X3\", \"观察X4\"],\n",
    "        \"变数Y\": [\"观察Y1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数Z\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "        \"变数A\": [\"观察Z1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数B\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "      } )\n",
    "display (框框)# A1 dict\n",
    "# 先弄字典, 再弄 框框 的写法片语\n",
    "字典 = {\n",
    "        \"变数X\": [\"观察X1\", \"观察X2\", \"观察X3\", \"观察X4\"],    \n",
    "        \"变数Y\": [\"观察Y1\", \"观察Y2\", \"观察Y3\", \"观察Y4\"],\n",
    "        \"变数Z\": [\"观察Z1\", \"观察Z2\", \"观察Z3\", \"观察Z4\"],\n",
    "       }\n",
    "\n",
    "框框 = pd.DataFrame ( 字典 )\n",
    "框框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    变数a   变数b   变数c   变数d\n",
      "0  观察X1  观察Y1  观察Z1  观察Z1\n",
      "1  观察X2  观察Y2  观察Z2  观察Z2\n",
      "2  观察X3  观察Y3  观察Z3  观察Z3\n",
      "3  观察X4  观察Y4  观察Z4  观察Z4\n",
      "181013040\n"
     ]
    }
   ],
   "source": [
    "# A1 print\n",
    "# 在ipynb用 print比较不上看，因为是文字text输出为主\n",
    "print (框框)  \n",
    "print (181013040) # 打印别的东西"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数X</th>\n",
       "      <th>变数Y</th>\n",
       "      <th>变数Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数X   变数Y   变数Z\n",
       "0  观察X1  观察Y1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A1 print\n",
    "# 在ipynb用 print比较不上看，因为是文字text输出为主\n",
    "print (框框)  \n",
    "print (181013040) # 打印别的东西# A1 display\n",
    "# 在ipynb可用 display 比较上看\n",
    "\n",
    "from IPython.display import display, HTML\n",
    "# 從 IPython.display 模塊 導入使用 display和HTML\n",
    "display (框框)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数a</th>\n",
       "      <th>变数b</th>\n",
       "      <th>变数c</th>\n",
       "      <th>变数d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数a   变数b   变数c   变数d\n",
       "0  观察X1  观察Y1  观察Z1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4  观察Z4"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A1 display   在ipynb可用 display 比较上看\n",
    "# 在上方尝试用print打印框框\n",
    "from IPython.display import display, HTML# 练习代码并记住即可\n",
    "# 從 IPython.display 模塊 導入使用 display和HTML\n",
    "display (框框)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 练习A1_post-框框框的课堂后练习\n",
    "\n",
    "老手有彩蛋项目可实践"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数X</th>\n",
       "      <th>变数Y</th>\n",
       "      <th>变数Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>观察X4</td>\n",
       "      <td>观察Y4</td>\n",
       "      <td>观察Z4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数X   变数Y   变数Z\n",
       "0  观察X1  观察Y1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3\n",
       "3  观察X4  观察Y4  观察Z4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A1 bonus\n",
    "# 已有此字典, 你能用代码生产同样的框框吗？\n",
    "字典 = {\n",
    "        \"变数\": [\"观察1\", \"观察2\", \"观察3\"],\n",
    "       }\n",
    "\n",
    "# 你的代码\n",
    "\n",
    "框框"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>变数1</th>\n",
       "      <th>变数2</th>\n",
       "      <th>变数3</th>\n",
       "      <th>变数4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>观察X1</td>\n",
       "      <td>观察Y1</td>\n",
       "      <td>观察Z1</td>\n",
       "      <td>观察Z1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>观察X2</td>\n",
       "      <td>观察Y2</td>\n",
       "      <td>观察Z2</td>\n",
       "      <td>观察Z2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>观察X3</td>\n",
       "      <td>观察Y3</td>\n",
       "      <td>观察Z3</td>\n",
       "      <td>观察Z3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    变数1   变数2   变数3   变数4\n",
       "0  观察X1  观察Y1  观察Z1  观察Z1\n",
       "1  观察X2  观察Y2  观察Z2  观察Z2\n",
       "2  观察X3  观察Y3  观察Z3  观察Z3"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A1 bonus\n",
    "# 框框是众多序列变数的观察\n",
    "# 若要做机器学习，测试模型的时候，造数据行为\n",
    "# 已有此字典, 你能用代码生产同样的框框吗？\n",
    "字典 = {\n",
    "        \"变数\": [\"观察1\", \"观察2\", \"观察3\"],\n",
    "       }\n",
    "\n",
    "# 你的代码\n",
    "字典 = {\n",
    "        \"变数1\": [\"观察X1\", \"观察X2\", \"观察X3\"],    \n",
    "        \"变数2\": [\"观察Y1\", \"观察Y2\", \"观察Y3\"],\n",
    "        \"变数3\": [\"观察Z1\", \"观察Z2\", \"观察Z3\"],\n",
    "        \"变数4\": [\"观察Z1\", \"观察Z2\", \"观察Z3\"],\n",
    "       }\n",
    "框框 = pd.DataFrame ( 字典 )\n",
    "框框"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "新手请认真记忆并操练，\n",
    "#### 练习A2-**框框框**(DataFrame)的取变数成 **系列** (Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    观察X1\n",
       "1    观察X2\n",
       "2    观察X3\n",
       "3    观察X4\n",
       "Name: 变数X, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A2 Series\n",
    "# first slice\n",
    "框框 [\"变数X\"]  # [] 像字典取值, 改值从列表升级为有**索引的序列**\n",
    "# object 对象/物件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['观察X1', '观察X2', '观察X3', '观察X4'], dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A2 Series values\n",
    "框框 [\"变数X\"].values # 值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=4, step=1)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A2 Series index\n",
    "框框 [\"变数X\"].index # 索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 2, 3]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(框框 [\"变数X\"].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "变数X    观察X4\n",
       "变数Y    观察Y4\n",
       "变数Z    观察Z4\n",
       "Name: 3, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A2 DataFrame .loc[]\n",
    "# 用 .loc[] 取列, 相当於所有变数的某一次观察\n",
    "框框.loc[3]   # loc = location  row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['观察X1', '观察X2', '观察X3', '观察X4']\n",
      "['观察X1', '观察X2', '观察X3', '观察X4']\n",
      "['观察X1', '观察X2', '观察X3', '观察X4']\n",
      "[0, 1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "# A2 Series to_list()\n",
    "# 降阶打击, 变列表的方法\n",
    "print ( 框框 [\"变数X\"].to_list() )    \n",
    "print ( list(框框 [\"变数X\"]) )\n",
    "print ( list(框框 [\"变数X\"].values) )\n",
    "print ( list(框框 [\"变数X\"].index) )\n",
    "\n",
    "# 区分读/写代码: \n",
    "# 你可以挑一个你比较常用的\"说法\", \n",
    "# 但你看到别人不同的说法时, 你需要知道是同一件事"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![01_table_dataframe.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/01_table_dataframe.svg)\n",
    "### 框框框的小结\n",
    "以下为廖老师示范，其它小结需要自己做小结\n",
    "1. 对数据科学来说，表格数据的习惯是变数variables与观察observations\n",
    "2. 在Pandas框框框的建构来说，就是可以把变数和观察用索引的方式使用\n",
    "3. 框框框的字典取的是某个变数所有观察, 用.loc[]取數次观察的所有变数\n",
    "  * .loc[] 取  观察, 行 column\n",
    "  * [\"\"] 取  变数, 列 row\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![02_io_readwrite.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/02_io_readwrite.svg)\n",
    "## 如何读写表格数据？\n",
    "读读读，写写写，数据科学家不想浪费时间编程去处理不同数据格式，所以pandas集成了常用的现成的文件格式或数据源（csv，excel，sql，json，parquet等）..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 框框框的课堂练习\n",
    "新手请认真记忆并操练 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 读读读的代码片语\n",
    "读读读的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "```python\n",
    "\n",
    "读到csv = pd.read_csv(\"路径档案名\", encoding=\"utf8\")\n",
    "读到tsv = pd.read_csv(\"路径档案名\", encoding=\"utf8\", sep=\"\\t\")\n",
    "读到excel = pd.read_excel(\"路径档案名\", sheet_name=\"分页名称\")\n",
    "```\n",
    "\n",
    "代码片语说明\n",
    "\n",
    "你可否查到[最新的文档](https://pandas.pydata.org/pandas-docs/version/1.0.2/)的说明，用markdown语法编辑在此，并看一些有什麽参数可以使用，自己学者做笔记\n",
    "\n",
    "* pd.read_csv\n",
    "* pd.read_excel\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Infor</td>\n",
       "      <td>Infor</td>\n",
       "      <td>3500</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Jim Schaper</td>\n",
       "      <td>2002</td>\n",
       "      <td>Golden Gate Capital, Koch Equity Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>3400</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Adam Bowen, James Monsees, Kevin Burns, Tim Da...</td>\n",
       "      <td>2015</td>\n",
       "      <td>M13, Timothy Davis, Evolution VC Partners, Tig...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名       企业名称   Company Name  估值（亿人民币）  国家   城市     行业  \\\n",
       "0   1       蚂蚁金服  Ant Financial     10000  中国   杭州   金融科技   \n",
       "1   2       字节跳动      Bytedance      5000  中国   北京  媒体和娱乐   \n",
       "2   3       滴滴出行   Didi Chuxing      3600  中国   北京   共享经济   \n",
       "3   4      Infor          Infor      3500  美国   纽约    云计算   \n",
       "4   5  JUUL Labs      JUUL Labs      3400  美国  旧金山    消费品   \n",
       "\n",
       "                                             掌门人/创始人  成立年份  \\\n",
       "0                                                井贤栋  2014   \n",
       "1                                                张一鸣  2012   \n",
       "2                                                 程维  2012   \n",
       "3                                        Jim Schaper  2002   \n",
       "4  Adam Bowen, James Monsees, Kevin Burns, Tim Da...  2015   \n",
       "\n",
       "                                              部分投资机构  \n",
       "0                                     春华资本、中投海外、红杉资本  \n",
       "1                                红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2                             腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "3       Golden Gate Capital, Koch Equity Development  \n",
       "4  M13, Timothy Davis, Evolution VC Partners, Tig...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B1 20春_pandas_week02_hurun_unicorn.tsv\n",
    "df = pd.read_csv(\"20春_pandas_week02_hurun_unicorn.tsv\", encoding=\"utf8\", sep=\"\\t\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>region</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名  企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "0   1  蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1   2  字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2   3  滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "3   6   陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "4  11  微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "\n",
       "                   部分投资机构   region  \n",
       "0          春华资本、中投海外、红杉资本  环杭州湾大湾区  \n",
       "1     红杉资本、海纳亚洲、纪源资本、启明创投    渤海大湾区  \n",
       "2  腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本    渤海大湾区  \n",
       "3     摩根士丹利、中银集团、国泰君安（香港）  环杭州湾大湾区  \n",
       "4             腾讯、华平投资、淡马锡   粤港澳大湾区  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B2 20春_pandas_week02_hurun_unicorn_more.csv\n",
    "df = pd.read_csv(\"20春_pandas_week02_hurun_unicorn_more.csv\", encoding=\"utf8\", sep=\"\\t\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Infor</td>\n",
       "      <td>Infor</td>\n",
       "      <td>3500</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Jim Schaper</td>\n",
       "      <td>2002</td>\n",
       "      <td>Golden Gate Capital, Koch Equity Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>3400</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Adam Bowen, James Monsees, Kevin Burns, Tim Da...</td>\n",
       "      <td>2015</td>\n",
       "      <td>M13, Timothy Davis, Evolution VC Partners, Tig...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名       企业名称   Company Name  估值（亿人民币）  国家   城市     行业  \\\n",
       "0   1       蚂蚁金服  Ant Financial     10000  中国   杭州   金融科技   \n",
       "1   2       字节跳动      Bytedance      5000  中国   北京  媒体和娱乐   \n",
       "2   3       滴滴出行   Didi Chuxing      3600  中国   北京   共享经济   \n",
       "3   4      Infor          Infor      3500  美国   纽约    云计算   \n",
       "4   5  JUUL Labs      JUUL Labs      3400  美国  旧金山    消费品   \n",
       "\n",
       "                                             掌门人/创始人  成立年份  \\\n",
       "0                                                井贤栋  2014   \n",
       "1                                                张一鸣  2012   \n",
       "2                                                 程维  2012   \n",
       "3                                        Jim Schaper  2002   \n",
       "4  Adam Bowen, James Monsees, Kevin Burns, Tim Da...  2015   \n",
       "\n",
       "                                              部分投资机构  \n",
       "0                                     春华资本、中投海外、红杉资本  \n",
       "1                                红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2                             腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "3       Golden Gate Capital, Koch Equity Development  \n",
       "4  M13, Timothy Davis, Evolution VC Partners, Tig...  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B3 20春_pandas_week02_hurun_unicorn.xlsx\n",
    "df = pd.read_excel(\"20春_pandas_week02_hurun_unicorn.xlsx\", encoding=\"utf8\", sheet_name=\"独角兽\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# B4 df.head()\n",
    "# B5 df.info()\n",
    "# B6 df.shape\n",
    "# B7 df.describe(include=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Infor</td>\n",
       "      <td>Infor</td>\n",
       "      <td>3500</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Jim Schaper</td>\n",
       "      <td>2002</td>\n",
       "      <td>Golden Gate Capital, Koch Equity Development</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业      掌门人/创始人  成立年份  \\\n",
       "0   1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技          井贤栋  2014   \n",
       "1   2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐          张一鸣  2012   \n",
       "2   3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济           程维  2012   \n",
       "3   4  Infor          Infor      3500  美国  纽约    云计算  Jim Schaper  2002   \n",
       "\n",
       "                                         部分投资机构  \n",
       "0                                春华资本、中投海外、红杉资本  \n",
       "1                           红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2                        腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "3  Golden Gate Capital, Koch Equity Development  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B4 df.head()\n",
    "# 前几名\n",
    "df.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 494 entries, 0 to 493\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   排名            494 non-null    int64 \n",
      " 1   企业名称          494 non-null    object\n",
      " 2   Company Name  494 non-null    object\n",
      " 3   估值（亿人民币）      494 non-null    int64 \n",
      " 4   国家            494 non-null    object\n",
      " 5   城市            494 non-null    object\n",
      " 6   行业            494 non-null    object\n",
      " 7   掌门人/创始人       494 non-null    object\n",
      " 8   成立年份          494 non-null    int64 \n",
      " 9   部分投资机构        494 non-null    object\n",
      "dtypes: int64(3), object(7)\n",
      "memory usage: 38.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# B5 df.info()\n",
    "# 可以列出这个数据框的所有变数\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(494, 10)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B6 df.shape\n",
    "# 框框横跟宽\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>494.000000</td>\n",
       "      <td>494</td>\n",
       "      <td>494</td>\n",
       "      <td>494.000000</td>\n",
       "      <td>494</td>\n",
       "      <td>494</td>\n",
       "      <td>494</td>\n",
       "      <td>494</td>\n",
       "      <td>494.000000</td>\n",
       "      <td>494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>494</td>\n",
       "      <td>494</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24</td>\n",
       "      <td>120</td>\n",
       "      <td>25</td>\n",
       "      <td>485</td>\n",
       "      <td>NaN</td>\n",
       "      <td>489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Tongdun</td>\n",
       "      <td>NaN</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>-</td>\n",
       "      <td>NaN</td>\n",
       "      <td>红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>206</td>\n",
       "      <td>81</td>\n",
       "      <td>68</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>180.977733</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>238.805668</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2011.234818</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>91.073191</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>623.158537</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.792477</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>84.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>224.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>264.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>264.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                排名  企业名称 Company Name      估值（亿人民币）   国家   城市    行业 掌门人/创始人  \\\n",
       "count   494.000000   494          494    494.000000  494  494   494     494   \n",
       "unique         NaN   494          494           NaN   24  120    25     485   \n",
       "top            NaN  滴滴出行      Tongdun           NaN   中国   北京  电子商务       -   \n",
       "freq           NaN     1            1           NaN  206   81    68       3   \n",
       "mean    180.977733   NaN          NaN    238.805668  NaN  NaN   NaN     NaN   \n",
       "std      91.073191   NaN          NaN    623.158537  NaN  NaN   NaN     NaN   \n",
       "min       1.000000   NaN          NaN     70.000000  NaN  NaN   NaN     NaN   \n",
       "25%      84.000000   NaN          NaN     70.000000  NaN  NaN   NaN     NaN   \n",
       "50%     224.000000   NaN          NaN    100.000000  NaN  NaN   NaN     NaN   \n",
       "75%     264.000000   NaN          NaN    200.000000  NaN  NaN   NaN     NaN   \n",
       "max     264.000000   NaN          NaN  10000.000000  NaN  NaN   NaN     NaN   \n",
       "\n",
       "               成立年份 部分投资机构  \n",
       "count    494.000000    494  \n",
       "unique          NaN    489  \n",
       "top             NaN   红杉资本  \n",
       "freq            NaN      3  \n",
       "mean    2011.234818    NaN  \n",
       "std        3.792477    NaN  \n",
       "min     2000.000000    NaN  \n",
       "25%     2009.000000    NaN  \n",
       "50%     2012.000000    NaN  \n",
       "75%     2014.000000    NaN  \n",
       "max     2019.000000    NaN  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# B7 df.describe(include=\"all\")\n",
    "df.describe(include=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# B4 df.head()\n",
    "# 前几名\n",
    "df.head(4)# B5 df.info()\n",
    "# 可以列出这个数据框的所有变数\n",
    "df.info()# B6 df.shape\n",
    "# 框框横跟宽\n",
    "df.shape# B7 df.describe(include=\"all\")\n",
    "df.describe(include=\"all\")# B8 df.to_markdown()\n",
    "# B9 df.to_html()\n",
    "# B10 df.to_json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'<table border=\"1\" class=\"dataframe\">\\n  <thead>\\n    <tr style=\"text-align: right;\">\\n      <th></th>\\n      <th>排名</th>\\n      <th>企业名称</th>\\n      <th>Company Name</th>\\n      <th>估值（亿人民币）</th>\\n      <th>国家</th>\\n      <th>城市</th>\\n      <th>行业</th>\\n      <th>掌门人/创始人</th>\\n      <th>成立年份</th>\\n      <th>部分投资机构</th>\\n    </tr>\\n  </thead>\\n  <tbody>\\n    <tr>\\n      <th>0</th>\\n      <td>1</td>\\n      <td>蚂蚁金服</td>\\n      <td>Ant Financial</td>\\n      <td>10000</td>\\n      <td>中国</td>\\n      <td>杭州</td>\\n      <td>金融科技</td>\\n      <td>井贤栋</td>\\n      <td>2014</td>\\n      <td>春华资本、中投海外、红杉资本</td>\\n    </tr>\\n    <tr>\\n      <th>1</th>\\n      <td>2</td>\\n      <td>字节跳动</td>\\n      <td>Bytedance</td>\\n      <td>5000</td>\\n      <td>中国</td>\\n      <td>北京</td>\\n      <td>媒体和娱乐</td>\\n      <td>张一鸣</td>\\n      <td>2012</td>\\n      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\\n    </tr>\\n    <tr>\\n      <th>2</th>\\n      <td>3</td>\\n      <td>滴滴出行</td>\\n      <td>Didi Chuxing</td>\\n      <td>3600</td>\\n      <td>中国</td>\\n      <td>北京</td>\\n      <td>共享经济</td>\\n      <td>程维</td>\\n      <td>2012</td>\\n      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\\n    </tr>\\n  </tbody>\\n</table>'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# html格式表格\n",
    "df.head(3).to_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       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Brown,\\\\u00a0Steven McKnight\",\"69\":\"\\\\u5218\\\\u81ea\\\\u9e3f\",\"70\":\"John Bicket, Sanjit Biswas\",\"71\":\"Thierry Cruanes, Marcin Zukowski, Benoit Dageville\",\"72\":\"Daniel Macklin,\\\\u00a0Ian Brady,\\\\u00a0James Finnigan,\\\\u00a0Michael Cagney\",\"73\":\"Kristo Kaarmann, Taavet Hinrikus\",\"74\":\"Albert Albert,\\\\u00a0Derianto Kusuma,\\\\u00a0Ferry Unardi\",\"75\":\"Ariel Cohen,\\\\u00a0Ilan Twig\",\"76\":\"\\\\u5468\\\\u5251\",\"77\":\"\\\\u859b\\\\u654f\",\"78\":\"\\\\u6c88\\\\u6656\",\"79\":\"\\\\u4f55\\\\u5c0f\\\\u9e4f\",\"80\":\"\\\\u5de6\\\\u6656\",\"81\":\"Deepinder Goyal,\\\\u00a0Pankaj Chaddah\",\"82\":\"Jason Austin, Lex Greensill\",\"83\":\"Jeffrey Kaditz,\\\\u00a0Max Levchin,\\\\u00a0Nathan Gettings\",\"84\":\"Ankur Kothari,\\\\u00a0Mihir Shukla,\\\\u00a0Neeti Mehta\",\"85\":\"\\\\u4e8e\\\\u51ac\",\"86\":\"Henrique Dubugras,\\\\u00a0Pedro Franceschi\",\"87\":\"\\\\u5f20\\\\u6960\\\\u8d53\",\"88\":\"Cameron Adams,\\\\u00a0Cliff Obrecht,\\\\u00a0Melanie Perkins\",\"89\":\"\\\\u7530\\\\u6797\",\"90\":\"Jeremy Allaire,\\\\u00a0Sean Neville\",\"91\":\"\\\\u5468\\\\u66e6\",\"92\":\"Jay Kreps,\\\\u00a0Jun Rao,\\\\u00a0Neha Narkhede\",\"93\":\"\\\\u5218\\\\u8363\",\"94\":\"Ali Ghodsi,\\\\u00a0Andy Konwinski,\\\\u00a0Ion Stoica,\\\\u00a0Matei Zaharia,\\\\u00a0Patrick Wendell,\\\\u00a0Reynold Xin,\\\\u00a0Scott Shenker\",\"95\":\"\\\\u9648\\\\u5c11\\\\u6770\",\"96\":\"\\\\u6731\\\\u5149\",\"97\":\"Ryan Petersen\",\"98\":\"Doug Hirsch,\\\\u00a0Scott Marlette,\\\\u00a0Trevor Bezdek\",\"99\":\"\\\\u6768\\\\u78ca\",\"100\":\"\\\\u5218\\\\u4e16\\\\u9ad8\",\"101\":\"\\\\u4f59\\\\u5efa\\\\u519b\",\"102\":\"\\\\u4f59\\\\u51ef\",\"103\":\"\\\\u5f90\\\\u79c0\\\\u8d24\",\"104\":\"Fritz H. Wolff,\\\\u00a0Jim Davidson,\\\\u00a0Michael Marks\",\"105\":\"\\\\u80e1\\\\u6c38\",\"106\":\"\\\\u5f90\\\\u6b63\",\"107\":\"Gary Dolman,\\\\u00a0Jason Bates,\\\\u00a0Jonas Huckestein,\\\\u00a0Paul Rippon,\\\\u00a0Tom Blomfield\",\"108\":\"Maximilian Tayenthal,\\\\u00a0Valentin Stalf\",\"109\":\"Dave Ferguson, Jiajun Zhu\",\"110\":\"Joel Perlman,\\\\u00a0Rishi Khosla\",\"111\":\"Greg Wyler\",\"112\":\"Joshua Kushner,\\\\u00a0Mario Schlosser\",\"113\":\"Vijay Shekhar Sharma\",\"114\":\"William Hockey,\\\\u00a0Zachary Perret\",\"115\":\"Craig Courtemanche\",\"116\":\"\\\\u9f50\\\\u5411\\\\u4e1c\",\"117\":\"Alexis Ohanian,\\\\u00a0Steve Huffman\",\"118\":\"David Baszucki\",\"119\":\"Arvind Jain, Arvind Nithrakashyap, Bipul Sinha, Soham Mazumdar\",\"120\":\"\\\\u6c88\\\\u6d77\\\\u5bc5\",\"121\":\"Alex Fenkell,\\\\u00a0Jordan Katzman\",\"122\":\"\\\\u59da\\\\u519b\\\\u7ea2\",\"123\":\"Nandan Reddy,\\\\u00a0Rahul Jaimini,\\\\u00a0Sriharsha Majety\",\"124\":\"Eric Lefkofsky\",\"125\":\"Aman Narang,\\\\u00a0Jonathan Grimm,\\\\u00a0Steve Fredette\",\"126\":\"David Helgason,\\\\u00a0Joachim Ante,\\\\u00a0Nicholas Francis\",\"127\":\"\\\\u6bdb\\\\u5927\\\\u5e86\",\"128\":\"\\\\u7c73\\\\u96ef\\\\u5a1f\",\"129\":\"Bong Jin Kim\",\"130\":\"\\\\u6bdb\\\\u6587\\\\u8d85\",\"131\":\"\\\\u91d1\\\\u5149\\\\u78ca\",\"132\":\"\\\\u97e9\\\\u5764\",\"133\":\"\\\\u536b\\\\u4fca\",\"134\":\"\\\\u674e\\\\u52c7\",\"135\":\"Jesse Levinson,\\\\u00a0Tim Kentley-Klay\",\"136\":\"\\\\u4faf\\\\u5efa\\\\u5f6c\",\"137\":\"Anne Wojcicki,\\\\u00a0Linda Avey,\\\\u00a0Paul Cusenza\",\"138\":\"Zia Chishti\",\"139\":\"\\\\u9648\\\\u96ea\\\\u5cf0\",\"140\":\"Adam Foroughi,\\\\u00a0Andrew Karam,\\\\u00a0John Krystynak\",\"141\":\"\\\\u674e\\\\u6d9b\",\"142\":\"Dustin Moskovitz,\\\\u00a0Justin Rosenstein\",\"143\":\"Chris Urmson,\\\\u00a0J. Andrew Bagnell,\\\\u00a0Sterling Anderson\",\"144\":\"Al Goldstein,\\\\u00a0John Sun,\\\\u00a0Paul Zhang\",\"145\":\"Brent Gutekunst,\\\\u00a0Ivan Griffin,\\\\u00a0Ken Mulvany,\\\\u00a0Michael Brennan\",\"146\":\"Karthik Ganapathy, Ajay Kaushal, MN Srinivasu\",\"147\":\"\\\\u8d75\\\\u957f\\\\u9e4f\\\\u3001\\\\u4f55\\\\u4e00\",\"148\":\"Travis VanderZanden\",\"149\":\"Francis Nappez,\\\\u00a0Fr\\\\u00e9d\\\\u00e9ric Mazzella,\\\\u00a0Nicolas Brusson\",\"150\":\"Brendan Blumer\",\"151\":\"John Johnson,\\\\u00a0Jonah Peretti\",\"152\":\"\\\\u6bd5\\\\u798f\\\\u5eb7\",\"153\":\"\\\\u9648\\\\u5929\\\\u77f3\",\"154\":\"\\\\u7530\\\\u660e\",\"155\":\"Joseph M. DeSimone,\\\\u00a0Philip DeSimone\",\"156\":\"Henry Ward,\\\\u00a0Manu Kumar\",\"157\":\"Guillaume Pousaz\",\"158\":\"\\\\u674e\\\\u60f3\",\"159\":\"Chris Britt,\\\\u00a0Ryan King\",\"160\":\"Ingmar Hoerr\",\"161\":\"Dave Palmer,\\\\u00a0Emily Orton,\\\\u00a0Jack Stockdale,\\\\u00a0Nicole Eagan,\\\\u00a0Poppy Gustafsson\",\"162\":\"Jeff Kinsey,\\\\u00a0Theodore Bailey\",\"163\":\"Bhavesh Manglani,\\\\u00a0Kapil Bharati,\\\\u00a0Mohit Tandon,\\\\u00a0Sahil Barua,\\\\u00a0Suraj Saharan\",\"164\":\"Greg Orlowski,\\\\u00a0William Shu\",\"165\":\"Chris Schuh,\\\\u00a0Ely Sachs,\\\\u00a0Emanuel M. Sachs,\\\\u00a0John Hart,\\\\u00a0Jonah Myerberg,\\\\u00a0Ric Fulop,\\\\u00a0Rick Chin,\\\\u00a0Yet-Ming Chiang\",\"166\":\"Ed Park,\\\\u00a0Jeremy Delinsky,\\\\u00a0Todd Park\",\"167\":\"Dominic Williams\",\"168\":\"Jason Citron\",\"169\":\"Andr\\\\u00e9 Schw\\\\u00e4mmlein,\\\\u00a0Daniel Krauss,\\\\u00a0Jochen Engert\",\"170\":\"Girish Mathrubootham,\\\\u00a0Shan Krishnasamy\",\"171\":\"Dave Waiser,\\\\u00a0Roi More\",\"172\":\"Nigel Toon,\\\\u00a0Simon Knowles\",\"173\":\"Edward Kim,\\\\u00a0Joshua Reeves,\\\\u00a0Tomer London\",\"174\":\"Armon Dadgar,\\\\u00a0Mitchell Hashimoto\",\"175\":\"Charles A. Taylor,\\\\u00a0Christopher K. Zarins\",\"176\":\"Monte Casino,\\\\u00a0Patrick Brown\",\"177\":\"Herman Narula,\\\\u00a0Peter Lipka,\\\\u00a0Rob Whitehead\",\"178\":\"Moshe Yanai\",\"179\":\"David Elkington,\\\\u00a0Ken Krogue,\\\\u00a0Rob Christensen\",\"180\":\"Ben Nadel,\\\\u00a0Clark Valberg\",\"181\":\"\\\\u6768\\\\u79cb\\\\u747e\",\"182\":\"Gerald Blackie\",\"183\":\"\\\\u738b\\\\u80b2\\\\u6797\",\"184\":\"Benny Landa\",\"185\":\"Daniel Schreiber,\\\\u00a0Shai Wininger\",\"186\":\"Adam Zhang,\\\\u00a0Brad Bao,\\\\u00a0Charlie Gao,\\\\u00a0Toby Sun\",\"187\":\"\\\\u9648\\\\u7f61\",\"188\":\"Jason Gardner\",\"189\":\"\\\\u53f6\\\\u56fd\\\\u5bcc\",\"190\":\"Eran Zinman,\\\\u00a0Roy Mann\",\"191\":\"Michael A Liberty\",\"192\":\"Dhiraj C Rajaram\",\"193\":\"Patrick Soon-Shiong\",\"194\":\"Adam Ginsburg,\\\\u00a0David Wiesen,\\\\u00a0Madison Bell,\\\\u00a0Nirav Tolia,\\\\u00a0Prakash Janakiraman,\\\\u00a0Sarah Leary\",\"195\":\"Craig Weiss\",\"196\":\"Paolo Cerruti,\\\\u00a0Peter Carlsson\",\"197\":\"Gordon Sanghera,\\\\u00a0Hagan Bayley\",\"198\":\"Adam Bowen,\\\\u00a0James Monsees\",\"199\":\"\\\\u9648\\\\u5b87\",\"200\":\"\\\\u5f6d\\\\u519b \\\\u3001\\\\u697c\\\\u5929\\\\u57ce\",\"201\":\"Bastian Lehmann,\\\\u00a0Sam Street,\\\\u00a0Sean Plaice\",\"202\":\"Daisuke Okanohara,\\\\u00a0Toru Nishikawa\",\"203\":\"Louay Eldada,\\\\u00a0Yu Tianyue\",\"204\":\"Adam D\\\\u2019Angelo,\\\\u00a0Charlie Cheever\",\"205\":\"\\\\u6c6a\\\\u83b9\",\"206\":\"Sumant Sinha\",\"207\":\"Nikolay Storonsky,\\\\u00a0Vlad Yatsenko\",\"208\":\"Calvin French-Owen,\\\\u00a0Ian Storm Taylor,\\\\u00a0Ilya Volodarsky,\\\\u00a0Peter Reinhardt\",\"209\":\"Ara Mahdessian,\\\\u00a0Vahe Kuzoyan\",\"210\":\"Jeff Arnold,\\\\u00a0Mehmet Oz\",\"211\":\"Ragy Thomas\",\"212\":\"Anthony Casalena\",\"213\":\"Robert Simonds,\\\\u00a0William McGlashan\",\"214\":\"\\\\u5f20\\\\u8fd1\\\\u4e1c\",\"215\":\"\\\\u4fde\\\\u6c38\\\\u798f\",\"216\":\"Bradley Keywell\",\"217\":\"Andrew Hunt,\\\\u00a0David Gilboa,\\\\u00a0Jeffrey 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Collins\",\"223\":\"\\\\u8c37\\\\u5cf0\",\"224\":\"\\\\u5218\\\\u91d1\\\\u826f\",\"225\":\"\\\\u6c88\\\\u535a\\\\u9633\",\"226\":\"\\\\u80e1\\\\u4e1c\",\"227\":\"\\\\u5f20\\\\u6d77\\\\u4eae\",\"228\":\"\\\\u8c2d\\\\u9f99\",\"229\":\"\\\\u674e\\\\u950b\",\"230\":\"\\\\u5e94\\\\u4e66\\\\u5cad\",\"231\":\"\\\\u5f20\\\\u4e00\\\\u6625\",\"232\":\"\\\\u674e\\\\u6aac\",\"233\":\"\\\\u5218\\\\u5929\\\\u6587\",\"234\":\"\\\\u8f9b\\\\u5229\\\\u519b\",\"235\":\"\\\\u4f55\\\\u529b\",\"236\":\"\\\\u6c6a\\\\u5efa\\\\u56fd\",\"237\":\"\\\\u738b\\\\u5fd7\\\\u8c6a\",\"238\":\"\\\\u6d2a\\\\u6e05\\\\u534e\",\"239\":\"\\\\u5218\\\\u6960\",\"240\":\"\\\\u845b\\\\u5c9a\",\"241\":\"\\\\u59ec\\\\u6653\\\\u6668\",\"242\":\"\\\\u6731\\\\u4e00\\\\u95fb\",\"243\":\"\\\\u9ad8\\\\u7984\\\\u5cf0\",\"244\":\"\\\\u7530\\\\u5b81\",\"245\":\"\\\\u674e\\\\u5efa\\\\u5168\",\"246\":\"\\\\u89e3\\\\u5c45\\\\u5fd7\",\"247\":\"\\\\u8bb8\\\\u4ef0\\\\u5929\",\"248\":\"\\\\u5f20\\\\u52c7\",\"249\":\"\\\\u9ec4\\\\u5b8f\\\\u751f\",\"250\":\"\\\\u5c45\\\\u9759\",\"251\":\"\\\\u848b\\\\u97ec\",\"252\":\"\\\\u738b\\\\u56fd\\\\u5f6c\",\"253\":\"\\\\u9648\\\\u654f\",\"254\":\"\\\\u7f57\\\\u519b\",\"255\":\"\\\\u738b\\\\u5b66\\\\u96c6\",\"256\":\"\\\\u738b\\\\u73c2\",\"257\":\"\\\\u9ece\\\\u745e\\\\u521a\",\"258\":\"\\\\u674e\\\\u9769\",\"259\":\"\\\\u9648\\\\u9a70\",\"260\":\"\\\\u5f20\\\\u7ee7\\\\u5b66\",\"261\":\"\\\\u6731\\\\u660e\\\\u8dc3\",\"262\":\"\\\\u738b\\\\u4e1c\",\"263\":\"\\\\u5f20\\\\u97f6\\\\u5cf0\",\"264\":\"Ben Hindson,\\\\u00a0Serge Saxonov\",\"265\":\"\\\\u5218\\\\u7545\",\"266\":\"\\\\u6768\\\\u9675\\\\u6c5f\",\"267\":\"\\\\u6234\\\\u6587\\\\u6e0a\",\"268\":\"\\\\u5b59\\\\u96f7\",\"269\":\"Sebastian Betz,\\\\u00a0Tarek Muller\",\"270\":\"Ash Ashutosh,\\\\u00a0David Chang\",\"271\":\"Doug Dohring\",\"272\":\"Andrew Ofstad,\\\\u00a0Emmett Nicholas,\\\\u00a0Howie Liu\",\"273\":\"Jack Zhang\",\"274\":\"\\\\u674e\\\\u6587\\\\u535a\",\"275\":\"\\\\u5f20\\\\u52c7\",\"276\":\"Joseph Zwillinger,\\\\u00a0Tim Brown\",\"277\":\"Robert Edward Grant\",\"278\":\"\\\\u738b\\\\u62e5\\\\u519b\",\"279\":\"\\\\u5409\\\\u670b\\\\u677e\",\"280\":\"Daniel Saks,\\\\u00a0Nicolas Desmarais\",\"281\":\"Eugenio Pace,\\\\u00a0Matias Woloski\",\"282\":\"Matt Mullenweg\",\"283\":\"Michael Praeger\",\"284\":\"Jen Rubio,\\\\u00a0Steph Korey\",\"285\":\"\\\\u90dd\\\\u98de\",\"286\":\"\\\\u5f20\\\\u826f\\\\u4f26\",\"287\":\"Abhinay Choudhari,\\\\u00a0Hari Menon,\\\\u00a0Vipul Parekh,\\\\u00a0VS 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Astra International Tbk - TSO Salemba\",\"23\":\"Alibaba Group, SoftBank, Berkshire Hathaway, Sapphire Ventures, Mountain Capital, Ant Financial\",\"24\":\"\\\\u817e\\\\u8baf\",\"25\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u4eca\\\\u65e5\\\\u8d44\\\\u672c\\\\u3001IDG\\\\u3001\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\",\"26\":\"SoftBank Investment Advisers, Altos Ventures, Sequoia Capital, BlackRock Private Equity Partners, Softbank, Maverick Ventures\",\"27\":\"IDG\\\\u3001\\\\u601d\\\\u4f70\\\\u76ca\\\\u3001\\\\u8f6f\\\\u94f6\\\\u6d77\\\\u5916\",\"28\":\"Formation 8, GGV Capital, Founders Fund, DST Global, Temasek Holdings\",\"29\":\"DFJ, Andreessen Horowitz, Tiger Global Management, IVP, Bank of Tokyo-Mitsubishi\",\"30\":\"Illumina, ARCH Venture Partners, 6 Dimensions Capital, Ally Bridge Group, Hillhouse Capital Group\\\\u00a0, HuangPu River Capital\",\"31\":\"Y Combinator, Sequoia Capital, Kleiner Perkins, Andreessen Horowitz, Tiger Global Management, Coatue Management, D1 capital partners, Whole Foods Market\",\"32\":\"Index Ventures, New Enterprise Associates, DST Global\",\"33\":\"Volkswagen, Ford\",\"34\":\"\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\",\"35\":\"IDG\\\\u3001\\\\u601d\\\\u4f70\\\\u76ca\",\"36\":\"Softbank Investment Advisors, QVT Financial, Viking Global Investors, Novaquest Capital Management, RTW Investments LLC\",\"37\":\"\\\\u5149\\\\u5927\\\\u63a7\\\\u80a1\\\\u3001\\\\u6df1\\\\u521b\\\\u6295\",\"38\":\"Andreessen Horowitz, Franklin Templeton Investments,\\\\u00a0Geodesic Capital,\\\\u00a0IVP (Institutional Venture Partners), TPG, TPG Growth, Wellington Management\",\"39\":\"Indonusa Dwitama, East Ventures, CyberAgent Capital, Beenos Partners, Softbank Ventures Asia, SoftBank Telecom Corp, Softbank Investment Advsors\",\"40\":\"Denso, Softbank Investment Advisors, Toyota Motor Corporation\",\"41\":\"Earlybird Venture Capital, Capital G, Sequoia Capital, Coatue Management, Accel\",\"42\":\"Aarin Capital, Sequoia Capital India, Chan Zuckerberg Initiative, Sofina, Verlinvest, Tencent Holdings, Naspers, General Atlantic, Qatar Investment Authority, Sovereign Wealth Funds\",\"43\":\"\\\\u817e\\\\u8baf\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u5149\\\\u901f\\\\u4e2d\\\\u56fd\\\\u3001\\\\u9ad8\\\\u74f4\\\\u8d44\\\\u672c\\\\u3001\\\\u4e91\\\\u5cf0\\\\u57fa\\\\u91d1\\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\",\"44\":\"Tamasek Holdings, Alibaba Group, Google, Saudi Arabia\\'s Public Investment Fund, NTT Docomo\",\"45\":\"Tiger Global Management, Hyundai Motor Company, Kia Motors, Sequoia Capital India, SoftBank Capital, DST Global, Baillie Gifford, Vanguard, Softbank, Falcon Edge Capital, Tekne Capital, Yes Bank, Sachin Bansal, Temasek Holdings, China Eurasian Economic Cooperation Fund, Eternal Yield International, Steadview Capital, Tencent Holdings, Sailing Capital\",\"46\":\"\\\\u9f0e\\\\u6656\\\\u6295\\\\u8d44\\\\u3001IDG\\\\u3001\\\\u4e2d\\\\u91d1\\\\u516c\\\\u53f8\",\"47\":\"\\\\u4e91\\\\u950b\\\\u57fa\\\\u91d1\\\\u3001\\\\u4e91\\\\u5cad\\\\u6295\\\\u8d44\\\\u3001\\\\u4e2d\\\\u91d1\\\\u516c\\\\u53f8\",\"48\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u9ad8\\\\u76db\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\\\\u3001\\\\u9ad8\\\\u74f4\\\\u8d44\\\\u672c\",\"49\":\"Tencent Holdings\",\"50\":\"Alibaba Group, Temasek Holding, Tesco, Rocket Internet\",\"51\":\"Y Combinator, Menlo Ventures, JP Morgan Partners\",\"52\":\"Greenoaks Capital, SoftBank, SoftBank Investment Advisers, Huazhu Hotels Group, Grab, Didi Chuxing, Airbnb\",\"53\":\"Core Innovation Capital, IDG Capital, Santander InnoVentures, SBI Investment\",\"54\":\"Ford Motor Company, Amazon\",\"55\":\"Artemis, Lewis Trust Group, Kohlberg Kravis Roberts, Balderton Capital, Merian Global Investors, William Currie Group\",\"56\":\"DN Capital, Piton Capital, DST Global, Princeville Global, SoftBank Investment Advisers\",\"57\":\"IVP (Institutional Venture Partners), Wellington Management, Fidelity, SoftBank Investment Advisers, Qatar Investment Authority\",\"58\":\"QED Investors, Susquehanna Growth Equity, CapitalG, SV Angel, Silver Lake Partners\",\"59\":\"Evergrande Health Industry Group, Birch Lake Partners\",\"60\":\"Zeev Ventures, Sequoia Capital, GGV Capital, New Enterprise Associates, ICONIQ Capital\",\"61\":\"Flagship Pioneering, Alaska Permanent Fund, Activant Capital, Investment Corporation of Dubai (ICD), Baillie Gifford\",\"62\":\"Investment AB \\\\u00d6resund, Sequoia Capital, General Atlantic, Creandum, Anders Holch Povlsen, Visa, Permira, H&M, Snoop Dogg\",\"63\":\"\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\\\\u3001\\\\u8054\\\\u60f3\\\\u4e4b\\\\u661f\\\\u3001\\\\u5efa\\\\u94f6\\\\u56fd\\\\u9645\\\\u3001\\\\u8682\\\\u8681\\\\u91d1\\\\u670d \\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\",\"64\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001DST\\\\u3001\\\\u4eac\\\\u4e1c\",\"65\":\"Alsop Louie Partners, Spark Capital, IVP (Institutional Venture Partners)\",\"66\":\"Sequoia Capital, Tiger Global Management, Founders Fund, Goldman Sachs, DST Global, Fortress Investment Group, Tencent Holdings\",\"67\":\"Khosla Ventures, GGV Capital, Access Technology Ventures, Norwest Venture Partners, Lennar Corporation, SoftBank Investment Advisers, General Atlantic\",\"68\":\"Tiger Global Management, L Catterton, Fidelity, Kleiner Perkins, True Ventures, Wellington Management\",\"69\":\"\\\\u4e2d\\\\u4fe1\\\\u4ea7\\\\u4e1a\\\\u57fa\\\\u91d1\\\\u3001\\\\u57fa\\\\u77f3\\\\u8d44\\\\u672c\\\\u3001IDG\",\"70\":\"Andreessen Horowitz, General Catalyst\",\"71\":\"Sutter Hill Ventures, Redpoint, Altimeter Capital, ICONIQ Capital, Sequoia Capital\",\"72\":\"Baseline Ventures, Morgan Stanley, The Bancorp, East West Bank, Discovery Capital, Third Point Ventures, Softbank, Silver Lake Partners, Qatar Investment Authority\",\"73\":\"Seedcamp, IA Ventures\\\\u00a0, Valar Ventures, Index Ventures, Andreessen Horowitz, Baillie Gifford, IVP (Institutional Venture Partners)\\\\u00a0, JP Morgan, Lead Edge Capital, Merian Global Investors, LHV Ventures, NatWest Bank, Lone Pine Capital, Vitruvian Partners\",\"74\":\"East Ventures, Global Founders Capital, GIC, Expedia\",\"75\":\"Zeev Ventures, Lightspeed Venture Partners, Andreessen Horowitz, 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Founders Capital, Morgan Stanley, GIC, Thrive Capital, HVF Labs\",\"84\":\"Goldman Sachs, SoftBank Investment Advisers, Workday Ventures\",\"85\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\\\\u3001\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\\\\u3001\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u4e07\\\\u8fbe\\\\u9662\\\\u7ebf\\\\u3001\\\\u817e\\\\u8baf\",\"86\":\"Y Combinator, Ribbit Capital, DST Global, Barclays Investment Bank, Kleiner Perkins , Greenoaks Capital\",\"87\":\"\\\\u9526\\\\u6c5f\\\\u96c6\\\\u56e2\\\\u3001\\\\u66be\\\\u6f9c\\\\u8d44\\\\u672c\",\"88\":\"Felicis Ventures, Blackbird Ventures (Australia), Sequoia Capital, Bond\\\\u00a0, General Catalyst\",\"89\":\"\\\\u5149\\\\u9645\\\\u8d44\\\\u672c\\\\u3001IDG\",\"90\":\"Breyer Capital, IDG Capital, Bitmain, Goldman Sachs Principal Strategic Investments\",\"91\":\"\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u5143\\\\u79be\\\\u539f\\\\u70b9\\\\u3001\\\\u524d\\\\u6d77\\\\u5174\\\\u65fa\",\"92\":\"Benchmark, Index Ventures, Sequoia Capital\",\"93\":\"\\\\u963f\\\\u91cc\\\\u5f71\\\\u4e1a\",\"94\":\"Andreessen Horowitz, New Enterprise Associates\",\"95\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u5357\\\\u5c71\\\\u8d44\\\\u672c\",\"96\":\"TPG\\\\u3001\\\\u51ef\\\\u96f7\\\\u6295\\\\u8d44\\\\uff0c\\\\u6cf0\\\\u5eb7\\\\u96c6\\\\u56e2\\\\u3001\\\\u519c\\\\u94f6\\\\u56fd\\\\u9645\",\"97\":\"Founders Fund, DST Global, SF Express, SoftBank Investment Advisers\",\"98\":\"Silver Lake Partners\",\"99\":\"\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\\\\u3001\\\\u78d0\\\\u8c37\\\\u521b\\\\u6295\\\\u3001\\\\u6109\\\\u60a6\\\\u8d44\\\\u672c\\\\u3001\\\\u8682\\\\u8681\\\\u91d1\\\\u670d\",\"100\":\"\\\\u534e\\\\u76d6\\\\u8d44\\\\u672c\",\"101\":\"\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\\\\u3001Sierra 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Partners.\",\"110\":\"EDBI, SoftBank Investment Advisers, NIBC Bank N.V., Indiabulls Housing Finance Limited\",\"111\":\"SoftBank, Qualcomm Ventures, Virgin Group\",\"112\":\"Thrive Capital, Founders Fund, Formation 8, CapitalG, Fidelity, Alphabet\",\"113\":\"SoftBank, Alibaba Group\",\"114\":\"Spark Capital, New Enterprise Associates, Goldman Sachs Investment Partners, Index Ventures, Kleiner Perkins\",\"115\":\"Greater Pacific Capital, Bessemer Venture Partners, ICONIQ Capital, Dragoneer Investment Group, Tiger Global Management\",\"116\":\"IDG\\\\u8d44\\\\u672c\\\\u3001\\\\u4e2d\\\\u4fe1\\\\u5efa\\\\u6295\\\\u8d44\\\\u672c\\\\u3001\\\\u534e\\\\u5174\\\\u521b\\\\u6295\",\"117\":\"Y Combinator, Tencent Holdings\",\"118\":\"Index Ventures, Greylock Partners\\\\u00a0, Meritech Capital Partners, Tiger Global Management, Altos Ventures\\\\u00a0, First Round Capital\",\"119\":\"Lightspeed Venture Partners, Greylock Partners, Khosla Ventures, IVP (Institutional Venture Partners), Bain Capital Ventures\",\"120\":\"\\\\u5149\\\\u4fe1\\\\u8d44\\\\u672c\\\\u3001\\\\u5947\\\\u864e360\",\"121\":\"Clayton, Dubilier & Rice\",\"122\":\"\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u534e\\\\u5e73\\\\u6295\\\\u8d44\",\"123\":\"DST Global, Naspers, Bessemer Venture Partners, Accel, Norwest Venture Partners, SAIF Partners\",\"124\":\"New Enterprise Associates, T. Rowe Price, Baillie Gifford, Revolution\",\"125\":\"Bessemer Venture Partners, Generation Investment Management, T. Rowe Price, TCV, Lead Edge Capital, Tiger Global Management\",\"126\":\"Sequoia Capital, WetSummit Capital, DFJ Growth, Silver Lake Partners, Altimeter Capital\",\"127\":\"\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\",\"128\":\"\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\\\\u3001\\\\u4e91\\\\u950b\\\\u57fa\\\\u91d1\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\",\"129\":\"Bon Angels Venture Partners, Altos Ventures, Goldman Sachs, Hillhouse Capital Group\",\"130\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\\\\u3001\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\",\"131\":\"\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u9ad8\\\\u76db\",\"132\":\"\\\\u65b0\\\\u6d6a\\\\u3001\\\\u7ea2\\\\u70b9\\\\u521b\\\\u6295\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\",\"133\":\"\\\\u524d\\\\u6d77\\\\u68a7\\\\u6850\\\\u3001\\\\u4e2d\\\\u521b\\\\u6d77\\\\u6d0b\",\"134\":\"IDG\\\\u3001\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u534e\\\\u5e73\\\\u6295\\\\u8d44\",\"135\":\"DFJ, Lux Capital, Blackbird Ventures (Australia), Thomas Tull, Grok Ventures\",\"136\":\"\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\\\\u3001H Capital\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\",\"137\":\"Google, Johnson & Johnson Development Corporation, National Institutes of Health, Sequoia Capital, GlaxoSmithKline\",\"138\":\"Daniel Klueger, Global Asset Management\",\"139\":\"\\\\u4eac\\\\u4e1c\\\\u3001\\\\u51ef\\\\u8f89\\\\u57fa\\\\u91d1\\\\u3001\\\\u8fbe\\\\u6668\\\\u521b\\\\u6295\\\\u3001\\\\u5929\\\\u56fe\\\\u8d44\\\\u672c\\\\u3001\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\",\"140\":\"Orient Hontai Capital, Kohlberg Kravis Roberts\",\"141\":\"\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\",\"142\":\"Founders Fund, Y Combinator, Generation Investment Management\",\"143\":\"Greylock Partners, Sequoia Capital, Hyundai Motor Company, Index Ventures\",\"144\":\"General Atlantic, Kohler Kravis Roberts, Tiger Global Management, Jefferies\",\"145\":\"Woodford Investment Management\",\"146\":\"Visa, General Atlantic, TA Associates, Clearstone Venture Partners , SBI\",\"147\":\"Vertex Ventures, Black Hole Capital, Funcity Capital\",\"148\":\"Goldcrest Capital, Craft Ventures, Index Ventures, Valor Equity Partners, Sequoia Capital\",\"149\":\"Accel, Index Ventures, Insight Partners, Baring Vostok Capital Partners, SNCF\",\"150\":\"Peter Thiel\",\"151\":\"New Enterprise Associates, Andreessen Horowitz, NBCUniversal, Hearst Ventures, RRE Ventures\",\"152\":\"\\\\u4e00\\\\u6c7d\\\\u96c6\\\\u56e2\\\\u3001\\\\u542f\\\\u8fea\\\\u63a7\\\\u80a1\\\\u3001\\\\u5b81\\\\u5fb7\\\\u65f6\\\\u4ee3\",\"153\":\"\\\\u56fd\\\\u6295\\\\u521b\\\\u4e1a\\\\u3001\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u8054\\\\u60f3\\\\u521b\\\\u6295\",\"154\":\"\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u534e\\\\u4eba\\\\u6587\\\\u5316\",\"155\":\"Sequoia Capital, BMW i Ventures\\\\u00a0, GV, GE Ventures, Baillie Gifford, Madrone Capital Partners\",\"156\":\"Union Square Ventures, Spark Capital, Menlo Ventures,\\\\u00a0Social Capital, Meritech Capital Partners\\\\u00a0, Tribe Capital\",\"157\":\"DST Global\\\\u00a0, Insight Partners\",\"158\":\"\\\\u5229\\\\u6b27\\\\u80a1\\\\u4efd\\\\u3001\\\\u6e90\\\\u7801\\\\u8d44\\\\u672c\\\\u3001\\\\u660e\\\\u52bf\\\\u8d44\\\\u672c\",\"159\":\"Crosslink Capital, Aspect Ventures, Cathay Innovation, Menlo Ventures, DST Global,\",\"160\":\"DH Capital, Dievini Hopp Biotech Holding, OH Beteiligungen, Bill & Melinda Gates Foundation, Baillie Gifford, Baden-W\\\\u00fcrttembergische Versorgungsanstalt f\\\\u00fcr \\\\u00c4rzte\",\"161\":\"Invoke Capital Partners, Summit Partners, Kohlberg Kravis Roberts, Talis Capital, Vitruvian Partners\",\"162\":\"IVP (Institutional Venture Partners), Venrock, Fidelity\",\"163\":\"Nexus Venture Partners, Multiples Alternate Asset Management Private Limited,Tiger Global Management, The Carlyle Group, Fosun Group, Softbank, Canada Pension Plan Investment Board\",\"164\":\"Bridgepoint, Fidelity Management and Research Company\\\\u00a0, Amazon, DST Global, General Catalyst, T. 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Ventures, Swisscanto Invest, SoftBank Investment Advisers, Kees Koolen\",\"340\":\"Viking Global Investors\",\"341\":\"Goldman Sachs Principal Strategic Investments, Khosla Ventures, August Capital, GV, ICONIQ Capital\",\"342\":\"Lewis trust Group. Rocket Internet, Kinnevik AB\",\"343\":\"Thrive Capital, IVP (Institutional Venture Partners), Index Ventures, Sequoia Capital\",\"344\":\"Softbank Investment Advisors, General Atlantic\",\"345\":\"\\\\u631a\\\\u4fe1\\\\u8d44\\\\u672c\\\\u3001\\\\u5d07\\\\u5fb7\\\\u6295\\\\u8d44\\\\u3001DCM\\\\u4e2d\\\\u56fd\",\"346\":\"Norwest Venture Partners, Kaiser Permanente Ventures, Sorenson Capital, UPMC,OrbiMed\",\"347\":\"Foxconn Technology Group, Tencent Holdings, Bharti SoftBank, Tiger Global Management\",\"348\":\"Atomic, Thrive Capital, IVP (Institutional Venture Partners)\",\"349\":\"Ginko Ventures\",\"350\":\"\\\\u5fb7\\\\u540c\\\\u8d44\\\\u672c\\\\u3001\\\\u65b9\\\\u6b63\\\\u548c\\\\u751f\\\\u3001\\\\u5bcc\\\\u5764\\\\u6295\\\\u8d44\",\"351\":\"\\\\u77e5\\\\u5408\\\\u51fa\\\\u884c\\\\u3001\\\\u9e3f\\\\u5229\\\\u667a\\\\u6c47\",\"352\":\"\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\\\\u3001Intel Capital\\\\u3001\\\\u6d77\\\\u901a\\\\u5f00\\\\u5143\",\"353\":\"\\\\u6cdb\\\\u6d77\\\\u63a7\\\\u80a1\\\\u3001\\\\u590d\\\\u661f\\\\u9510\\\\u6b63\\\\u8d44\\\\u672c\",\"354\":\"\\\\u6c49\\\\u80fd\\\\u6295\\\\u8d44\\\\u3001\\\\u8f6f\\\\u94f6\\\\u3001\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\",\"355\":\"Illumina Ventures\",\"356\":\"\\\\u5929\\\\u5e9c\\\\u96c6\\\\u56e2\\\\u3001\\\\u946b\\\\u6839\\\\u8d44\\\\u672c\",\"357\":\"Greycroft, Premji Invest\",\"358\":\"Just Eat, Movile, Warehouse Investimentos, Naspers\",\"359\":\"\\\\u5929\\\\u56fe\\\\u8d44\\\\u672c\\\\u3001\\\\u8fbe\\\\u6668\\\\u521b\\\\u6295\\\\u3001\\\\u6b63\\\\u548c\\\\u5c9b\\\\u57fa\\\\u91d1\",\"360\":\"J.P. Morgan Asset Management, Andreessen Horowitz, General Catalyst, Accel, BlackRock\",\"361\":\"Softbank Capital, Kleiner Perkins, Sherpalo Ventures\",\"362\":\"Social Capital, Bessemer Venture Partners, ICONIQ Capital, Index Ventures, Kleiner Perkins\",\"363\":\"\\\\u817e\\\\u8baf\\\\u9886\\\\u6295\\\\uff0c\\\\u4eca\\\\u65e5\\\\u8d44\\\\u672c\",\"364\":\"Saban Capital Group, Access Industries\",\"365\":\"\\\\u542f\\\\u660e\\\\u521b\\\\u6295\\\\u3001GIC\\\\u3001\\\\u9ad8\\\\u76db\",\"366\":\"Ardian, Kohlberg Kravis Roberts, Tiger Global Management\",\"367\":\"Insight Partners, Vmware\",\"368\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u4e1c\\\\u65b9\\\\u5bcc\\\\u6d77\",\"369\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u541b\\\\u8054\\\\u8d44\\\\u672c\\\\u3001\\\\u9f0e\\\\u6656\\\\u6295\\\\u8d44\",\"370\":\"\\\\u5929\\\\u56fe\\\\u8d44\\\\u672c\\\\u3001\\\\u62db\\\\u94f6\\\\u56fd\\\\u9645\\\\u3001\\\\u6d59\\\\u6c5f\\\\u91d1\\\\u63a7\",\"371\":\"\\\\u666e\\\\u6d1b\\\\u65af\\\\u3001\\\\u65b0\\\\u5e0c\\\\u671b\\\\u3001\\\\u8fdc\\\\u6d0b\\\\u8d44\\\\u672c\",\"372\":\"IDG\\\\u8d44\\\\u672c\\\\u3001\\\\u4fe1\\\\u4e2d\\\\u5229\\\\u8d44\\\\u672c\\\\u3001\\\\u952e\\\\u6865\\\\u901a\\\\u8baf\",\"373\":\"BlueRun Ventures, Mohr Davidow Ventures, Thomvest Ventures, Guggenheim Securities, SoftBank Capital, Reverence Capital Partners, Credit Suisse\",\"374\":\"Index Ventures, Scale Venture Partners, IVP (Institutional Venture Partners), Greenoaks Capital\",\"375\":\"Berkshire Partners, Norwest Venture Partners\",\"376\":\"Kohlberg Kravis Roberts, Goldman Sachs, Elephant\",\"377\":\"\\\\u963f\\\\u91cc\\\\u5df4\\\\u5df4\\\\u3001\\\\u8054\\\\u60f3\\\\u4e4b\\\\u661f\\\\u3001\\\\u597d\\\\u672a\\\\u6765\\\\u6559\\\\u80b2\\\\u96c6\\\\u56e2\",\"378\":\"IDG\\\\u3001\\\\u6b4c\\\\u6590\\\\u8d44\\\\u4ea7\",\"379\":\"\\\\u6e05\\\\u6d41\\\\u8d44\\\\u672c\\\\u3001\\\\u8944\\\\u79be\\\\u8d44\\\\u672c\\\\u3001\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\",\"380\":\"\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\\\\u3001\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\",\"381\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u4e0a\\\\u6d77\\\\u7535\\\\u6c14\\\\u3001\\\\u5174\\\\u4e1a\\\\u8bc1\\\\u5238\",\"382\":\"Naspers\",\"383\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u5149\\\\u5927\\\\u5b9e\\\\u4e1a\\\\u3001\\\\u8d5b\\\\u4f2f\\\\u4e50\",\"384\":\"Viola Ventures, Insight Partners, Goldman Sachs Private Capital Investing, ClalTech\",\"385\":\"\\\\u4e2d\\\\u6295\\\\u516c\\\\u53f8\",\"386\":\"\\\\u817e\\\\u8baf\\\\u3001\\\\u6cdb\\\\u6d77\\\\u6295\\\\u8d44\\\\u3001\\\\u4e2d\\\\u4fe1\\\\u8d44\\\\u672c\",\"387\":\"\\\\u817e\\\\u8baf\\\\u3001\\\\u5f18\\\\u6bc5\\\\u6295\\\\u8d44\",\"388\":\"IDG Capital\",\"389\":\"SoftBank Investment Advisers, SoftBank, DOMO Invest\\\\u00a0, Monashees\\\\u00a0, Dragoneer Investment Group, IFC Venture Capital Group\\\\u00a0, Iporanga Investments, Qualcomm Ventures, Microsoft\",\"390\":\"IDG\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\",\"391\":\"T. Rowe Price, Andreessen Horowitz, Deutsche Telekom, Intex Ventures, Khosla Ventures\",\"392\":\"\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u817e\\\\u8baf\",\"393\":\"DST\\\\u3001IDG\\\\u3001\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\\\\u3001DCM\",\"394\":\"Sequoia Capita, Lehman Brothers, Tenaya Capital, Wellington Management, NTT Data\",\"395\":\"Silicon Valley Bank, Goldman Sachs, Searchlight Capital Partners\",\"396\":\"Avenir Growth Capital, Eurazeo Prime Ventures\",\"397\":\"Koch Disruptive Technologies, T. Rowe Price, Hewlett Packard Enterprise, Khosla ventures, Andreessen Horowitz\",\"398\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\",\"399\":\"CITIC Securities\",\"400\":\"Hinduja Group, Leonardo DiCaprio, Venture Kick\",\"401\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u5206\\\\u4eab\\\\u6295\\\\u8d44\",\"402\":\"\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u6d77\\\\u7eb3\\\\u4e9a\\\\u6d32\",\"403\":\"\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u771f\\\\u683c\\\\u57fa\\\\u91d1\\\\u3001\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\",\"404\":\"Edison Partners,Greenspring Associates\",\"405\":\"Social Capital, Lightspeed Venture Partners, Accel, ICONIQ Capital\",\"406\":\"-\",\"407\":\"\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u534e\\\\u5174\\\\u8d44\\\\u672c\\\\u3001\\\\u5929\\\\u56fe\\\\u8d44\\\\u672c\\\\u3001\\\\u4eca\\\\u65e5\\\\u8d44\\\\u672c\",\"408\":\"\\\\u62db\\\\u94f6\\\\u56fd\\\\u9645\\\\u3001\\\\u56fd\\\\u6295\\\\u521b\\\\u65b0\",\"409\":\"T. Rowe Price, Warburg Pincus, Jackson Square Ventures\",\"410\":\"Matrix Partners India, Tata Sons Ltd, SoftBank, Tiger Global Management\",\"411\":\"Goldman Sachs Investment Partners, Kleiner Perkins, Kinnevik AB, Silver Lake Kraftwerk, Temasek Holdings, Battery Ventures, Lakestar, New Enterprise Associates, Hasso Plattner Ventures\",\"412\":\"The Carlyle Group, Benchmark, GV, Redmile Group, J.P. Morgan Asset Management, Maverick Ventures, Oak Investment Partners\",\"413\":\"Insight Partners\",\"414\":\"\\\\u8682\\\\u8681\\\\u91d1\\\\u670d\\\\u3001\\\\u8d5b\\\\u5bcc\\\\u6295\\\\u8d44\\\\u3001\\\\u677e\\\\u79be\\\\u8d44\\\\u672c\",\"415\":\"Clal Insurance Enterprises Holdings\\\\u00a0, Meitav Investment House, Intel Capital\",\"416\":\"Mayfield Fund, Trinity Ventures, DFJ Growth, Spark Capital, Lone Pine Capital\",\"417\":\"Armilar Venture Partners, North Bridge Venture Partners & Growth Equity, Goldman Sachs, Kohlberg Kravis Roberts\",\"418\":\"Mitsubishi Corp\",\"419\":\"Softbank Investment Advisors\",\"420\":\"ONE Luxury Group, Eurazeo\",\"421\":\"DST\\\\u3001\\\\u864e\\\\u6251\\\\u4f53\\\\u80b2\\\\u3001\\\\u666e\\\\u601d\\\\u8d44\\\\u672c\",\"422\":\"SoftBank Investment Advisors, Wellington Management, Premji Invest, Tiger Global Management, Inventus Capital Partners\",\"423\":\"\\\\u4e39\\\\u4e30\\\\u8d44\\\\u672c\\\\u3001\\\\u8f6f\\\\u94f6\\\\u4e2d\\\\u56fd\\\\u8d44\\\\u672c\",\"424\":\"Yuan Capital, Harbin Gloria Pharmaceuticals, Lycos Ventures\",\"425\":\"Trifecta Capital Advisors, Tiger Global Management, InnoVen Capital, Brand Capital, Kinnevik AB, Warburg Pincus, NGP Capital, Norwest Venture Partners, Omidyar Network\",\"426\":\"Accel, New Enterprise Associates\",\"427\":\"SoftBank, SoftBank Investment Advisers, Y Combinator, Andreessen Horowitz, Sequoia Capital, Delivery Hero, DST Global\",\"428\":\"\\\\u9ad8\\\\u76db\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u6ef4\\\\u6ef4\\\\u3001\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\",\"429\":\"\\\\u631a\\\\u4fe1\\\\u8d44\\\\u672c\",\"430\":\"Bain Capital Ventures, Highland Capital Partners, Kleiner Perkins, American Express Ventures, TCV, Fidelity Management and Research Company, Novel TMT Ventures, Blue Pool Capital, Temasek Holdings, Franklin Templeton Investments\",\"431\":\"500 Startups, K2 Global\",\"432\":\"SAIF Partners, Warburg Pincus\",\"433\":\"Bessemer Venture Partners, Data Collective DCVC, Future Fund\",\"434\":\"Drive Capital, Ribbit Capital, Redpoint, Tiger Global Management\",\"435\":\"QuarterMoore, Rotunda Capital Partners, Fifth Third Bancorp, Nima Capital, SUEZ Environnement, Promecap, NZ Super Fund\",\"436\":\"Jackson Square Ventures, JMI Equity, General Atlantic, Lightspeed Venture Partners\\\\u00a0, T. Rowe Price,\",\"437\":\"GIC, Tiger Global Management, Nexus Venture Partners, Helion Venture Partners\",\"438\":\"\\\\u767e\\\\u5ea6\\\\u3001\\\\u851a\\\\u6765\\\\u8d44\\\\u672c\",\"439\":\"\\\\u817e\\\\u8baf\\\\u3001\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\\\\u3001IDG\\\\u3001\\\\u7f8e\\\\u56e2\\\\u70b9\\\\u8bc4\",\"440\":\"Sutter Hill Ventures, Daimler\",\"441\":\"\\\\u542f\\\\u660e\\\\u521b\\\\u6295\",\"442\":\"\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001GIC\\\\u3001\\\\u7eaa\\\\u6e90\\\\u8d44\\\\u672c\",\"443\":\"Tao Capital Partners, Valor Equity Partners\",\"444\":\"Nvidia GPU Ventures, Tencent Holdings, Walden Venture Capital\",\"445\":\"DST Global, General Atlantic, GGV Capital, Battey Ventures\",\"446\":\"Greylock Partners, Accel, Sequoia Capital, DFJ Growth, Sapphire Ventures, Battery Ventures\",\"447\":\"Fidelity, Revolution, T. Rowe Price\",\"448\":\"Mitsubishi UFJ Financial Group, Standard Chartered Bank, BNP Paribas Private Equity\",\"449\":\"Fidelity Management and Research Company, Pitango Venture Capital, Marker, Evergreen Venture Partners\",\"450\":\"Viking Global Investors, Storm Ventures, DFJ, Salesforce Ventures\",\"451\":\"\\\\u8f6f\\\\u94f6\\\\u4e2d\\\\u56fd\\\\u3001\\\\u9ea6\\\\u987f\\\\u6295\\\\u8d44\\\\u3001\\\\u5317\\\\u6781\\\\u5149\\\\u521b\\\\u6295\",\"452\":\"Alibaba Group, DFJ\",\"453\":\"Matrix Partners, Rho Capital Partners, Shining Capital\",\"454\":\"\\\\u817e\\\\u8baf\\\\u3001\\\\u78a7\\\\u6842\\\\u56ed\\\\u521b\\\\u6295\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\",\"455\":\"General Catalyst, Institutional Venture Partners, Wellington Management, L Catterton, Glade Brook Capital Partners\",\"456\":\"Lightspeed Venture Partners, Sapphire Ventures, Khosla Ventures, General Catalysts\",\"457\":\"CapitalG, Baillie Gifford, Javelin Venture Partners, Sequoia Capital\",\"458\":\"Simone Investment Managers, NHM Invesment Corp, Kohlberg Kravis Roberts, Anchor Equity Partners\",\"459\":\"Altos Ventures, Goodwater Capital, GIC, Kleiner Perkins, Sequoia Capital China, Ribbit Capital\",\"460\":\"PayPal, Notion, Kite Ventures, Scentan Ventures, Data Collective DCVC, Wipro Ventures, Goldman Sachs Principal Strategic Investments\\\\u00a0, RTP Global, PSP Investments\",\"461\":\"GCP Capital Partners\",\"462\":\"Kleiner Perkins, SK Holdings, August Capital, IAC\",\"463\":\"Sina, Composite Capital Management\",\"464\":\"DCM\\\\u3001\\\\u8d1d\\\\u5854\\\\u65af\\\\u66fc\\\\u3001\\\\u541b\\\\u8054\\\\u8d44\\\\u672c\",\"465\":\"Lightspeed Venture Partners, DST Global\",\"466\":\"Bertelsmann, Andreessen Horowitz, CRV\",\"467\":\"\\\\u542f\\\\u660e\\\\u521b\\\\u6295\\\\u3001\\\\u9ad8\\\\u901a\",\"468\":\"\\\\u534e\\\\u5e73\\\\u6295\\\\u8d44\",\"469\":\"Softbank Investment Advisors, Blackrock, TIAA, Madrone Capital Partners, NanoDimension\",\"470\":\"Salesforce Ventures, Sutter Hill Ventures\",\"471\":\"NBC Universal, General Atlantic, Accel, Khosla Ventures\",\"472\":\"Bessemer Venture Partners, Thrive Capital, OpenView Venture Partners, Insight Partners, Brookfield Asset Management\",\"473\":\"\\\\u65b0\\\\u5929\\\\u57df\\\\u8d44\\\\u672c\\\\u3001\\\\u5149\\\\u4fe1\\\\u8d44\\\\u672c\\\\u3001IDG\\\\u3001\\\\u542f\\\\u660e\\\\u521b\\\\u6295\",\"474\":\"Gemini Israel Ventures, Scale Venture Partners, Greenspring Associates, Insight Partners, EDBI\",\"475\":\"TOM\\\\u96c6\\\\u56e2\\\\u3001Khazanah\\\\u3001IFC\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\",\"476\":\"\\\\u6d77\\\\u901a\\\\u5f00\\\\u5143\\\\u3001\\\\u5317\\\\u6781\\\\u5149\\\\u521b\\\\u6295\",\"477\":\"IDG\\\\u3001\\\\u8d5b\\\\u5bcc\\\\u57fa\\\\u91d1\\\\u3001\\\\u767e\\\\u5ea6\",\"478\":\"\\\\u7ca4\\\\u6c11\\\\u6295\\\\u3001\\\\u539a\\\\u6734\\\\u6295\\\\u8d44\\\\u3001\\\\u80e1\\\\u6da6\\\\u767e\\\\u5bcc\",\"479\":\"Partners Investment, Sky Lake Investment, Booking Holdings, GIC\",\"480\":\"\\\\u4f17\\\\u4fe1\\\\u65c5\\\\u6e38\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u521b\\\\u65b0\\\\u5de5\\\\u573a\",\"481\":\"\\\\u6d8c\\\\u94e7\\\\u6295\\\\u8d44\\\\u3001\\\\u6c47\\\\u80fd\\\\u91d1\\\\u878d\\\\u3001\\\\u78d0\\\\u77f3\\\\u8d44\\\\u672c\",\"482\":\"\\\\u51e4\\\\u51f0\\\\u3001\\\\u5c0f\\\\u7c73\\\\u3001IDG\",\"483\":\"\\\\u7f8e\\\\u56e2\\\\u70b9\\\\u8bc4\\\\u3001\\\\u817e\\\\u8baf\\\\u3001\\\\u8d1d\\\\u5854\\\\u65af\\\\u66fc\",\"484\":\"\\\\u535a\\\\u88d5\\\\u8d44\\\\u672c\\\\u3001\\\\u539a\\\\u6734\\\\u6295\\\\u8d44\\\\u3001\\\\u666e\\\\u6d1b\\\\u65af\\\\u3001\\\\u6e90\\\\u7801\\\\u8d44\\\\u672c\\\\u3001\\\\u9f0e\\\\u6656\\\\u6295\\\\u8d44\",\"485\":\"\\\\u8fdc\\\\u955c\\\\u521b\\\\u6295\\\\u3001\\\\u8d5b\\\\u5bcc\\\\u57fa\\\\u91d1\",\"486\":\"\\\\u9ad8\\\\u74f4\\\\u8d44\\\\u672c\\\\u3001\\\\u6668\\\\u5174\\\\u8d44\\\\u672c\\\\u3001\\\\u8f6f\\\\u94f6\\\\u4e2d\\\\u56fd\",\"487\":\"\\\\u541b\\\\u8054\\\\u8d44\\\\u672c\\\\u3001\\\\u6155\\\\u534e\\\\u6295\\\\u8d44\",\"488\":\"\\\\u534e\\\\u5e73\\\\u6295\\\\u8d44\\\\u3001\\\\u7ea2\\\\u6749\\\\u8d44\\\\u672c\\\\u3001\\\\u7ecf\\\\u7eac\\\\u4e2d\\\\u56fd\",\"489\":\"GPI Capital, GSO Capital Partners\",\"490\":\"\\\\u987a\\\\u4e3a\\\\u8d44\\\\u672c\\\\u3001\\\\u8fbe\\\\u6668\\\\u521b\\\\u6295\\\\u3001\\\\u534e\\\\u5e73\\\\u6295\\\\u8d44\",\"491\":\"\\\\u817e\\\\u8baf\",\"492\":\"Sequoia Capital, Visionnaire Ventures, Katalyst.Ventures\",\"493\":\"IVP (Institutional Venture Partners)\"}}'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#json格式\n",
    "df.to_json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'排名': {'count': 494.0,\n",
       "  'mean': 180.97773279352228,\n",
       "  'std': 91.07319075981641,\n",
       "  'min': 1.0,\n",
       "  '25%': 84.0,\n",
       "  '50%': 224.0,\n",
       "  '75%': 264.0,\n",
       "  'max': 264.0},\n",
       " '估值（亿人民币）': {'count': 494.0,\n",
       "  'mean': 238.80566801619435,\n",
       "  'std': 623.1585372633193,\n",
       "  'min': 70.0,\n",
       "  '25%': 70.0,\n",
       "  '50%': 100.0,\n",
       "  '75%': 200.0,\n",
       "  'max': 10000.0},\n",
       " '成立年份': {'count': 494.0,\n",
       "  'mean': 2011.2348178137652,\n",
       "  'std': 3.7924771092178786,\n",
       "  'min': 2000.0,\n",
       "  '25%': 2009.0,\n",
       "  '50%': 2012.0,\n",
       "  '75%': 2014.0,\n",
       "  'max': 2019.0}}"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# B11 df.to_dict()\n",
    "# B12 df.to_sql()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'排名': {0: 1,\n",
       "  1: 2,\n",
       "  2: 3,\n",
       "  3: 4,\n",
       "  4: 5,\n",
       "  5: 6,\n",
       "  6: 6,\n",
       "  7: 8,\n",
       "  8: 9,\n",
       "  9: 10,\n",
       "  10: 11,\n",
       "  11: 12,\n",
       "  12: 12,\n",
       "  13: 14,\n",
       "  14: 15,\n",
       "  15: 15,\n",
       "  16: 15,\n",
       "  17: 15,\n",
       "  18: 19,\n",
       "  19: 20,\n",
       "  20: 20,\n",
       "  21: 20,\n",
       "  22: 23,\n",
       "  23: 23,\n",
       "  24: 25,\n",
       "  25: 25,\n",
       "  26: 25,\n",
       "  27: 25,\n",
       "  28: 25,\n",
       "  29: 30,\n",
       "  30: 30,\n",
       "  31: 30,\n",
       "  32: 30,\n",
       "  33: 34,\n",
       "  34: 34,\n",
       "  35: 34,\n",
       "  36: 34,\n",
       "  37: 34,\n",
       "  38: 34,\n",
       "  39: 34,\n",
       "  40: 34,\n",
       "  41: 34,\n",
       "  42: 43,\n",
       "  43: 43,\n",
       "  44: 43,\n",
       "  45: 43,\n",
       "  46: 43,\n",
       "  47: 43,\n",
       "  48: 43,\n",
       "  49: 50,\n",
       "  50: 50,\n",
       "  51: 50,\n",
       "  52: 50,\n",
       "  53: 50,\n",
       "  54: 50,\n",
       "  55: 50,\n",
       "  56: 57,\n",
       "  57: 57,\n",
       "  58: 57,\n",
       "  59: 57,\n",
       "  60: 57,\n",
       "  61: 57,\n",
       "  62: 57,\n",
       "  63: 57,\n",
       "  64: 57,\n",
       "  65: 57,\n",
       "  66: 57,\n",
       "  67: 57,\n",
       "  68: 57,\n",
       "  69: 57,\n",
       "  70: 57,\n",
       "  71: 57,\n",
       "  72: 57,\n",
       "  73: 57,\n",
       "  74: 57,\n",
       "  75: 57,\n",
       "  76: 57,\n",
       "  77: 57,\n",
       "  78: 57,\n",
       "  79: 57,\n",
       "  80: 57,\n",
       "  81: 57,\n",
       "  82: 83,\n",
       "  83: 84,\n",
       "  84: 84,\n",
       "  85: 84,\n",
       "  86: 84,\n",
       "  87: 84,\n",
       "  88: 84,\n",
       "  89: 84,\n",
       "  90: 84,\n",
       "  91: 84,\n",
       "  92: 84,\n",
       "  93: 84,\n",
       "  94: 84,\n",
       "  95: 84,\n",
       "  96: 84,\n",
       "  97: 84,\n",
       "  98: 84,\n",
       "  99: 84,\n",
       "  100: 84,\n",
       "  101: 84,\n",
       "  102: 84,\n",
       "  103: 84,\n",
       "  104: 84,\n",
       "  105: 84,\n",
       "  106: 84,\n",
       "  107: 84,\n",
       "  108: 84,\n",
       "  109: 84,\n",
       "  110: 84,\n",
       "  111: 84,\n",
       "  112: 84,\n",
       "  113: 84,\n",
       "  114: 84,\n",
       "  115: 84,\n",
       "  116: 84,\n",
       "  117: 84,\n",
       "  118: 84,\n",
       "  119: 84,\n",
       "  120: 84,\n",
       "  121: 84,\n",
       "  122: 84,\n",
       "  123: 84,\n",
       "  124: 84,\n",
       "  125: 84,\n",
       "  126: 84,\n",
       "  127: 84,\n",
       "  128: 84,\n",
       "  129: 84,\n",
       "  130: 84,\n",
       "  131: 84,\n",
       "  132: 84,\n",
       "  133: 84,\n",
       "  134: 84,\n",
       "  135: 84,\n",
       "  136: 84,\n",
       "  137: 138,\n",
       "  138: 138,\n",
       "  139: 138,\n",
       "  140: 138,\n",
       "  141: 138,\n",
       "  142: 138,\n",
       "  143: 138,\n",
       "  144: 138,\n",
       "  145: 138,\n",
       "  146: 138,\n",
       "  147: 138,\n",
       "  148: 138,\n",
       "  149: 138,\n",
       "  150: 138,\n",
       "  151: 138,\n",
       "  152: 138,\n",
       "  153: 138,\n",
       "  154: 138,\n",
       "  155: 138,\n",
       "  156: 138,\n",
       "  157: 138,\n",
       "  158: 138,\n",
       "  159: 138,\n",
       "  160: 138,\n",
       "  161: 138,\n",
       "  162: 138,\n",
       "  163: 138,\n",
       "  164: 138,\n",
       "  165: 138,\n",
       "  166: 138,\n",
       "  167: 138,\n",
       "  168: 138,\n",
       "  169: 138,\n",
       "  170: 138,\n",
       "  171: 138,\n",
       "  172: 138,\n",
       "  173: 138,\n",
       "  174: 138,\n",
       "  175: 138,\n",
       "  176: 138,\n",
       "  177: 138,\n",
       "  178: 138,\n",
       "  179: 138,\n",
       "  180: 138,\n",
       "  181: 138,\n",
       "  182: 138,\n",
       "  183: 138,\n",
       "  184: 138,\n",
       "  185: 138,\n",
       "  186: 138,\n",
       "  187: 138,\n",
       "  188: 138,\n",
       "  189: 138,\n",
       "  190: 138,\n",
       "  191: 138,\n",
       "  192: 138,\n",
       "  193: 138,\n",
       "  194: 138,\n",
       "  195: 138,\n",
       "  196: 138,\n",
       "  197: 138,\n",
       "  198: 138,\n",
       "  199: 138,\n",
       "  200: 138,\n",
       "  201: 138,\n",
       "  202: 138,\n",
       "  203: 138,\n",
       "  204: 138,\n",
       "  205: 138,\n",
       "  206: 138,\n",
       "  207: 138,\n",
       "  208: 138,\n",
       "  209: 138,\n",
       "  210: 138,\n",
       "  211: 138,\n",
       "  212: 138,\n",
       "  213: 138,\n",
       "  214: 138,\n",
       "  215: 138,\n",
       "  216: 138,\n",
       "  217: 138,\n",
       "  218: 138,\n",
       "  219: 138,\n",
       "  220: 138,\n",
       "  221: 138,\n",
       "  222: 138,\n",
       "  223: 224,\n",
       "  224: 224,\n",
       "  225: 224,\n",
       "  226: 224,\n",
       "  227: 224,\n",
       "  228: 224,\n",
       "  229: 224,\n",
       "  230: 224,\n",
       "  231: 224,\n",
       "  232: 224,\n",
       "  233: 224,\n",
       "  234: 224,\n",
       "  235: 224,\n",
       "  236: 224,\n",
       "  237: 224,\n",
       "  238: 224,\n",
       "  239: 224,\n",
       "  240: 224,\n",
       "  241: 224,\n",
       "  242: 224,\n",
       "  243: 224,\n",
       "  244: 224,\n",
       "  245: 224,\n",
       "  246: 224,\n",
       "  247: 224,\n",
       "  248: 224,\n",
       "  249: 224,\n",
       "  250: 224,\n",
       "  251: 224,\n",
       "  252: 224,\n",
       "  253: 224,\n",
       "  254: 224,\n",
       "  255: 224,\n",
       "  256: 224,\n",
       "  257: 224,\n",
       "  258: 224,\n",
       "  259: 224,\n",
       "  260: 224,\n",
       "  261: 224,\n",
       "  262: 224,\n",
       "  263: 264,\n",
       "  264: 264,\n",
       "  265: 264,\n",
       "  266: 264,\n",
       "  267: 264,\n",
       "  268: 264,\n",
       "  269: 264,\n",
       "  270: 264,\n",
       "  271: 264,\n",
       "  272: 264,\n",
       "  273: 264,\n",
       "  274: 264,\n",
       "  275: 264,\n",
       "  276: 264,\n",
       "  277: 264,\n",
       "  278: 264,\n",
       "  279: 264,\n",
       "  280: 264,\n",
       "  281: 264,\n",
       "  282: 264,\n",
       "  283: 264,\n",
       "  284: 264,\n",
       "  285: 264,\n",
       "  286: 264,\n",
       "  287: 264,\n",
       "  288: 264,\n",
       "  289: 264,\n",
       "  290: 264,\n",
       "  291: 264,\n",
       "  292: 264,\n",
       "  293: 264,\n",
       "  294: 264,\n",
       "  295: 264,\n",
       "  296: 264,\n",
       "  297: 264,\n",
       "  298: 264,\n",
       "  299: 264,\n",
       "  300: 264,\n",
       "  301: 264,\n",
       "  302: 264,\n",
       "  303: 264,\n",
       "  304: 264,\n",
       "  305: 264,\n",
       "  306: 264,\n",
       "  307: 264,\n",
       "  308: 264,\n",
       "  309: 264,\n",
       "  310: 264,\n",
       "  311: 264,\n",
       "  312: 264,\n",
       "  313: 264,\n",
       "  314: 264,\n",
       "  315: 264,\n",
       "  316: 264,\n",
       "  317: 264,\n",
       "  318: 264,\n",
       "  319: 264,\n",
       "  320: 264,\n",
       "  321: 264,\n",
       "  322: 264,\n",
       "  323: 264,\n",
       "  324: 264,\n",
       "  325: 264,\n",
       "  326: 264,\n",
       "  327: 264,\n",
       "  328: 264,\n",
       "  329: 264,\n",
       "  330: 264,\n",
       "  331: 264,\n",
       "  332: 264,\n",
       "  333: 264,\n",
       "  334: 264,\n",
       "  335: 264,\n",
       "  336: 264,\n",
       "  337: 264,\n",
       "  338: 264,\n",
       "  339: 264,\n",
       "  340: 264,\n",
       "  341: 264,\n",
       "  342: 264,\n",
       "  343: 264,\n",
       "  344: 264,\n",
       "  345: 264,\n",
       "  346: 264,\n",
       "  347: 264,\n",
       "  348: 264,\n",
       "  349: 264,\n",
       "  350: 264,\n",
       "  351: 264,\n",
       "  352: 264,\n",
       "  353: 264,\n",
       "  354: 264,\n",
       "  355: 264,\n",
       "  356: 264,\n",
       "  357: 264,\n",
       "  358: 264,\n",
       "  359: 264,\n",
       "  360: 264,\n",
       "  361: 264,\n",
       "  362: 264,\n",
       "  363: 264,\n",
       "  364: 264,\n",
       "  365: 264,\n",
       "  366: 264,\n",
       "  367: 264,\n",
       "  368: 264,\n",
       "  369: 264,\n",
       "  370: 264,\n",
       "  371: 264,\n",
       "  372: 264,\n",
       "  373: 264,\n",
       "  374: 264,\n",
       "  375: 264,\n",
       "  376: 264,\n",
       "  377: 264,\n",
       "  378: 264,\n",
       "  379: 264,\n",
       "  380: 264,\n",
       "  381: 264,\n",
       "  382: 264,\n",
       "  383: 264,\n",
       "  384: 264,\n",
       "  385: 264,\n",
       "  386: 264,\n",
       "  387: 264,\n",
       "  388: 264,\n",
       "  389: 264,\n",
       "  390: 264,\n",
       "  391: 264,\n",
       "  392: 264,\n",
       "  393: 264,\n",
       "  394: 264,\n",
       "  395: 264,\n",
       "  396: 264,\n",
       "  397: 264,\n",
       "  398: 264,\n",
       "  399: 264,\n",
       "  400: 264,\n",
       "  401: 264,\n",
       "  402: 264,\n",
       "  403: 264,\n",
       "  404: 264,\n",
       "  405: 264,\n",
       "  406: 264,\n",
       "  407: 264,\n",
       "  408: 264,\n",
       "  409: 264,\n",
       "  410: 264,\n",
       "  411: 264,\n",
       "  412: 264,\n",
       "  413: 264,\n",
       "  414: 264,\n",
       "  415: 264,\n",
       "  416: 264,\n",
       "  417: 264,\n",
       "  418: 264,\n",
       "  419: 264,\n",
       "  420: 264,\n",
       "  421: 264,\n",
       "  422: 264,\n",
       "  423: 264,\n",
       "  424: 264,\n",
       "  425: 264,\n",
       "  426: 264,\n",
       "  427: 264,\n",
       "  428: 264,\n",
       "  429: 264,\n",
       "  430: 264,\n",
       "  431: 264,\n",
       "  432: 264,\n",
       "  433: 264,\n",
       "  434: 264,\n",
       "  435: 264,\n",
       "  436: 264,\n",
       "  437: 264,\n",
       "  438: 264,\n",
       "  439: 264,\n",
       "  440: 264,\n",
       "  441: 264,\n",
       "  442: 264,\n",
       "  443: 264,\n",
       "  444: 264,\n",
       "  445: 264,\n",
       "  446: 264,\n",
       "  447: 264,\n",
       "  448: 264,\n",
       "  449: 264,\n",
       "  450: 264,\n",
       "  451: 264,\n",
       "  452: 264,\n",
       "  453: 264,\n",
       "  454: 264,\n",
       "  455: 264,\n",
       "  456: 264,\n",
       "  457: 264,\n",
       "  458: 264,\n",
       "  459: 264,\n",
       "  460: 264,\n",
       "  461: 264,\n",
       "  462: 264,\n",
       "  463: 264,\n",
       "  464: 264,\n",
       "  465: 264,\n",
       "  466: 264,\n",
       "  467: 264,\n",
       "  468: 264,\n",
       "  469: 264,\n",
       "  470: 264,\n",
       "  471: 264,\n",
       "  472: 264,\n",
       "  473: 264,\n",
       "  474: 264,\n",
       "  475: 264,\n",
       "  476: 264,\n",
       "  477: 264,\n",
       "  478: 264,\n",
       "  479: 264,\n",
       "  480: 264,\n",
       "  481: 264,\n",
       "  482: 264,\n",
       "  483: 264,\n",
       "  484: 264,\n",
       "  485: 264,\n",
       "  486: 264,\n",
       "  487: 264,\n",
       "  488: 264,\n",
       "  489: 264,\n",
       "  490: 264,\n",
       "  491: 264,\n",
       "  492: 264,\n",
       "  493: 264},\n",
       " '企业名称': {0: '蚂蚁金服',\n",
       "  1: '字节跳动',\n",
       "  2: '滴滴出行',\n",
       "  3: 'Infor',\n",
       "  4: 'JUUL Labs',\n",
       "  5: '爱彼迎',\n",
       "  6: '陆金所',\n",
       "  7: 'SpaceX',\n",
       "  8: 'WeWork',\n",
       "  9: 'Stripe',\n",
       "  10: '微众银行',\n",
       "  11: '菜鸟网络',\n",
       "  12: '京东数科',\n",
       "  13: '快手',\n",
       "  14: '大疆',\n",
       "  15: 'Grab',\n",
       "  16: 'Hulu',\n",
       "  17: 'Palantir Technologies',\n",
       "  18: 'DoorDash',\n",
       "  19: '比特大陆',\n",
       "  20: '京东物流',\n",
       "  21: 'Samumed',\n",
       "  22: 'GO-JEK',\n",
       "  23: 'Paytm',\n",
       "  24: '贝壳找房',\n",
       "  25: '车好多',\n",
       "  26: 'Coupang',\n",
       "  27: '平安医保科技',\n",
       "  28: 'Wish',\n",
       "  29: 'Coinbase',\n",
       "  30: 'GRAIL',\n",
       "  31: 'Instacart',\n",
       "  32: 'Robinhood',\n",
       "  33: 'Argo AI',\n",
       "  34: '美菜网',\n",
       "  35: '金融壹账通',\n",
       "  36: 'Roivant Sciences',\n",
       "  37: '苏宁金服',\n",
       "  38: 'Tanium',\n",
       "  39: 'Tokopedia',\n",
       "  40: 'Uber ATG',\n",
       "  41: 'UiPath',\n",
       "  42: 'BYJU’s',\n",
       "  43: '满帮',\n",
       "  44: 'Magic Leap',\n",
       "  45: 'Ola Cabs',\n",
       "  46: '商汤科技',\n",
       "  47: '神州优车',\n",
       "  48: '微医',\n",
       "  49: 'Bluehole',\n",
       "  50: 'Lazada',\n",
       "  51: 'Machine Zone',\n",
       "  52: 'OYO Rooms',\n",
       "  53: 'Ripple',\n",
       "  54: 'Rivian',\n",
       "  55: 'The Hut Group',\n",
       "  56: 'Auto1 Group',\n",
       "  57: 'Compass',\n",
       "  58: 'Credit Karma',\n",
       "  59: 'Faraday Future',\n",
       "  60: 'Houzz',\n",
       "  61: 'Indigo Agriculture',\n",
       "  62: 'Klarna',\n",
       "  63: '旷视科技',\n",
       "  64: '达达-京东到家',\n",
       "  65: 'Niantic',\n",
       "  66: 'Nubank',\n",
       "  67: 'OpenDoor Labs',\n",
       "  68: 'Peloton',\n",
       "  69: '柔宇科技',\n",
       "  70: 'Samsara Networks',\n",
       "  71: 'Snowflake Computing',\n",
       "  72: 'SoFi',\n",
       "  73: 'TransferWise',\n",
       "  74: 'Traveloka',\n",
       "  75: 'TripActions',\n",
       "  76: '优必选',\n",
       "  77: '联影医疗',\n",
       "  78: '威马汽车',\n",
       "  79: '小鹏汽车',\n",
       "  80: '自如',\n",
       "  81: 'Zomato',\n",
       "  82: 'Greensill',\n",
       "  83: 'Affirm',\n",
       "  84: 'Automation Anywhere',\n",
       "  85: '博纳影业',\n",
       "  86: 'Brex',\n",
       "  87: '嘉楠耘智',\n",
       "  88: 'Canva',\n",
       "  89: '银联商务',\n",
       "  90: 'Circle Internet Financial',\n",
       "  91: '云从科技',\n",
       "  92: 'Confluent',\n",
       "  93: '大地影院',\n",
       "  94: 'Databricks',\n",
       "  95: '斗鱼',\n",
       "  96: '度小满金融',\n",
       "  97: 'Flexport',\n",
       "  98: 'GoodRx',\n",
       "  99: '哈啰出行',\n",
       "  100: '复宏汉霖',\n",
       "  101: '喜马拉雅',\n",
       "  102: '地平线机器人',\n",
       "  103: '汇通达',\n",
       "  104: 'Katerra',\n",
       "  105: '跨越速运',\n",
       "  106: '每日优鲜',\n",
       "  107: 'Monzo',\n",
       "  108: 'N26',\n",
       "  109: 'Nuro',\n",
       "  110: 'OakNorth',\n",
       "  111: 'OneWeb',\n",
       "  112: 'Oscar Health',\n",
       "  113: 'Paytm Mall',\n",
       "  114: 'Plaid Technologies',\n",
       "  115: 'Procore Technologies',\n",
       "  116: '奇安信',\n",
       "  117: 'reddit',\n",
       "  118: 'Roblox',\n",
       "  119: 'Rubrik',\n",
       "  120: '奇点汽车',\n",
       "  121: 'SmileDirectClub',\n",
       "  122: '大搜车',\n",
       "  123: 'Swiggy',\n",
       "  124: 'Tempus',\n",
       "  125: 'Toast',\n",
       "  126: 'Unity Technologies',\n",
       "  127: '优客工场',\n",
       "  128: 'VIPKID',\n",
       "  129: 'Woowa Brothers',\n",
       "  130: '小红书',\n",
       "  131: '易果生鲜',\n",
       "  132: '一下科技',\n",
       "  133: '游侠汽车',\n",
       "  134: '猿辅导',\n",
       "  135: 'Zoox',\n",
       "  136: '作业帮',\n",
       "  137: '23andMe',\n",
       "  138: 'Afiniti',\n",
       "  139: '爱回收',\n",
       "  140: 'AppLovin',\n",
       "  141: 'APUS',\n",
       "  142: 'Asana',\n",
       "  143: 'Aurora',\n",
       "  144: 'Avant',\n",
       "  145: 'BenevolentAI',\n",
       "  146: 'BillDesk',\n",
       "  147: 'Binance',\n",
       "  148: 'Bird Rides',\n",
       "  149: 'BlaBlaCar',\n",
       "  150: 'Block.One',\n",
       "  151: 'Buzzfeed',\n",
       "  152: '拜腾汽车',\n",
       "  153: '寒武纪科技',\n",
       "  154: '灿星',\n",
       "  155: 'Carbon',\n",
       "  156: 'Carta',\n",
       "  157: 'Checkout.com',\n",
       "  158: '车和家',\n",
       "  159: 'Chime',\n",
       "  160: 'CureVac',\n",
       "  161: 'Darktrace',\n",
       "  162: 'Dataminr',\n",
       "  163: 'Delhivery',\n",
       "  164: 'Deliveroo',\n",
       "  165: 'Desktop Metal',\n",
       "  166: 'Devoted Health',\n",
       "  167: 'Dfinity',\n",
       "  168: 'Discord',\n",
       "  169: 'FlixBus',\n",
       "  170: 'Freshworks',\n",
       "  171: 'Gett',\n",
       "  172: 'Graphcore',\n",
       "  173: 'Gusto',\n",
       "  174: 'HashiCorp',\n",
       "  175: 'HeartFlow',\n",
       "  176: 'Impossible Foods',\n",
       "  177: 'Improbable',\n",
       "  178: 'Infinidat',\n",
       "  179: 'InsideSales.com',\n",
       "  180: 'InVision',\n",
       "  181: '准时达',\n",
       "  182: 'Kaseya',\n",
       "  183: '金山云',\n",
       "  184: 'Landa Digital Printing',\n",
       "  185: 'Lemonade',\n",
       "  186: 'Lime',\n",
       "  187: '马蜂窝',\n",
       "  188: 'Marqeta',\n",
       "  189: '名创优品',\n",
       "  190: 'Monday.com',\n",
       "  191: 'Mozido',\n",
       "  192: 'Mu Sigma',\n",
       "  193: 'NantOmics',\n",
       "  194: 'Nextdoor',\n",
       "  195: 'Njoy',\n",
       "  196: 'Northvolt',\n",
       "  197: 'Oxford Nanopore Technologies',\n",
       "  198: 'PAX',\n",
       "  199: 'PingPong',\n",
       "  200: '小马智行',\n",
       "  201: 'Postmates',\n",
       "  202: 'Preferred Networks',\n",
       "  203: 'Quanergy Systems',\n",
       "  204: 'Quora',\n",
       "  205: '雾芯科技',\n",
       "  206: 'ReNew Power',\n",
       "  207: 'Revolut',\n",
       "  208: 'Segment',\n",
       "  209: 'ServiceTitan',\n",
       "  210: 'Sharecare',\n",
       "  211: 'Sprinklr',\n",
       "  212: 'Squarespace',\n",
       "  213: 'STX Entertainment',\n",
       "  214: '苏宁体育',\n",
       "  215: '淘票票',\n",
       "  216: 'Uptake',\n",
       "  217: 'Warby Parker',\n",
       "  218: '依图科技',\n",
       "  219: 'Zenefits',\n",
       "  220: '知乎',\n",
       "  221: 'ZocDoc',\n",
       "  222: 'Zume',\n",
       "  223: '爱驰汽车',\n",
       "  224: '曹操专车',\n",
       "  225: '蛋壳公寓',\n",
       "  226: '亿邦国际',\n",
       "  227: '天际汽车',\n",
       "  228: '悦畅科技',\n",
       "  229: '高顿',\n",
       "  230: '英雄互娱',\n",
       "  231: '惠民网',\n",
       "  232: '天下秀',\n",
       "  233: '软通动力',\n",
       "  234: '京东健康',\n",
       "  235: '界面',\n",
       "  236: '孩子王',\n",
       "  237: '客路旅行',\n",
       "  238: '驴妈妈',\n",
       "  239: '蜜芽',\n",
       "  240: '魔方公寓',\n",
       "  241: '影谱科技',\n",
       "  242: '网易云音乐',\n",
       "  243: '纳恩博',\n",
       "  244: '盘石股份',\n",
       "  245: '全棉时代',\n",
       "  246: '日日顺',\n",
       "  247: 'SheIn',\n",
       "  248: '蜀海',\n",
       "  249: '开沃汽车',\n",
       "  250: '秦淮数据',\n",
       "  251: '同盾科技',\n",
       "  252: '土巴兔',\n",
       "  253: '途虎养车',\n",
       "  254: '途家网',\n",
       "  255: '涂鸦智能',\n",
       "  256: '微店',\n",
       "  257: '微鲸',\n",
       "  258: '药明明码',\n",
       "  259: '小猪短租',\n",
       "  260: '新潮传媒',\n",
       "  261: '猪八戒网',\n",
       "  262: '找钢网',\n",
       "  263: '百融金服',\n",
       "  264: '10X Genomics',\n",
       "  265: '一起作业',\n",
       "  266: '1919酒类直供',\n",
       "  267: '第四范式',\n",
       "  268: '玖富',\n",
       "  269: 'About You',\n",
       "  270: 'Actifio',\n",
       "  271: 'Age of Learning',\n",
       "  272: 'Airtable',\n",
       "  273: '空中云汇',\n",
       "  274: '岩心科技',\n",
       "  275: '阿里体育',\n",
       "  276: 'Allbirds',\n",
       "  277: 'Alphaeon Corporation',\n",
       "  278: '安能物流',\n",
       "  279: '安翰医疗',\n",
       "  280: 'AppDirect',\n",
       "  281: 'Auth0',\n",
       "  282: 'Automattic',\n",
       "  283: 'AvidXchange',\n",
       "  284: 'Away',\n",
       "  285: '斑马网络',\n",
       "  286: '贝贝网',\n",
       "  287: 'BigBasket',\n",
       "  288: 'Bill.com',\n",
       "  289: 'BitFury',\n",
       "  290: 'Bolt',\n",
       "  291: '波奇网',\n",
       "  292: '博郡汽车',\n",
       "  293: 'Branch',\n",
       "  294: 'Bukalapak',\n",
       "  295: 'Butterfly Network',\n",
       "  296: 'C3',\n",
       "  297: 'Cabify',\n",
       "  298: 'Calm.com',\n",
       "  299: '康众汽配',\n",
       "  300: 'Casper',\n",
       "  301: 'Celonis',\n",
       "  302: 'ChargePoint',\n",
       "  303: '车猫二手车',\n",
       "  304: '车置宝',\n",
       "  305: '春雨医生',\n",
       "  306: 'CloudFlare',\n",
       "  307: 'Clover Health',\n",
       "  308: 'Cohesity',\n",
       "  309: 'Collibra',\n",
       "  310: 'Como',\n",
       "  311: 'Convoy',\n",
       "  312: 'Coursera',\n",
       "  313: '哒哒英语',\n",
       "  314: '58到家',\n",
       "  315: 'DataRobot',\n",
       "  316: 'Dataxu',\n",
       "  317: 'Deezer',\n",
       "  318: '点融网',\n",
       "  319: 'Docker',\n",
       "  320: 'Doctolib',\n",
       "  321: 'DotC United',\n",
       "  322: 'DraftKings',\n",
       "  323: 'Dream11',\n",
       "  324: 'Druva',\n",
       "  325: '数梦工场',\n",
       "  326: '丁香园',\n",
       "  327: '易生金服',\n",
       "  328: '远景能源',\n",
       "  329: 'Evernote',\n",
       "  330: 'ezCater',\n",
       "  331: 'Fair',\n",
       "  332: '房多多',\n",
       "  333: '返利网',\n",
       "  334: '丰巢科技',\n",
       "  335: 'Formlabs',\n",
       "  336: '纷享销客',\n",
       "  337: 'G7',\n",
       "  338: '集奥聚合',\n",
       "  339: 'GetYourGuide',\n",
       "  340: 'Ginkgo BioWorks',\n",
       "  341: 'GitLab',\n",
       "  342: 'Global Fashion Group',\n",
       "  343: 'Glossier',\n",
       "  344: 'Gympass',\n",
       "  345: '好大夫在线',\n",
       "  346: 'Health Catalyst',\n",
       "  347: 'Hike',\n",
       "  348: 'Hims',\n",
       "  349: 'HMD',\n",
       "  350: '好享家',\n",
       "  351: '合众汽车',\n",
       "  352: '华云数据',\n",
       "  353: '慧科教育',\n",
       "  354: '沪江',\n",
       "  355: 'Human Longevity',\n",
       "  356: '碳云智能',\n",
       "  357: 'Icertis',\n",
       "  358: 'iFood',\n",
       "  359: '艾佳生活',\n",
       "  360: 'Illumio',\n",
       "  361: 'InMobi',\n",
       "  362: 'Intercom',\n",
       "  363: '谊品生鲜',\n",
       "  364: 'ironSource',\n",
       "  365: '麦奇教育科技',\n",
       "  366: 'Ivalua',\n",
       "  367: 'JFrog',\n",
       "  368: '酒仙网',\n",
       "  369: '执御信息',\n",
       "  370: '卷皮',\n",
       "  371: '驹马物流',\n",
       "  372: '九次方大数据',\n",
       "  373: 'Kabbage',\n",
       "  374: 'KeepTruckin',\n",
       "  375: 'Kendra Scott',\n",
       "  376: 'KnowBe4',\n",
       "  377: '作业盒子',\n",
       "  378: '氪空间',\n",
       "  379: '货拉拉',\n",
       "  380: '辣妈帮',\n",
       "  381: '零跑汽车',\n",
       "  382: 'letgo',\n",
       "  383: '连连数字',\n",
       "  384: 'Lightricks',\n",
       "  385: '零氪科技',\n",
       "  386: '联易融',\n",
       "  387: '柠萌影业',\n",
       "  388: 'Liquid Global',\n",
       "  389: 'Loggi',\n",
       "  390: '罗计物流',\n",
       "  391: 'Lookout',\n",
       "  392: '罗辑思维',\n",
       "  393: '脉脉',\n",
       "  394: 'MarkLogic',\n",
       "  395: 'MediaMath',\n",
       "  396: 'Meero',\n",
       "  397: 'Mesosphere',\n",
       "  398: '妙手医生',\n",
       "  399: 'Microvast',\n",
       "  400: 'MindMaze',\n",
       "  401: '明略科技',\n",
       "  402: '出门问问',\n",
       "  403: 'Momenta',\n",
       "  404: 'MoneyLion',\n",
       "  405: 'Netskope',\n",
       "  406: 'Nikola Motor Company',\n",
       "  407: '诺米',\n",
       "  408: '诺禾致源',\n",
       "  409: 'OfferUp',\n",
       "  410: 'Ola Electric',\n",
       "  411: 'Omio',\n",
       "  412: 'One Medical Group',\n",
       "  413: 'OneTrust',\n",
       "  414: '奥比中光',\n",
       "  415: 'OrCam Technologies',\n",
       "  416: 'Outreach',\n",
       "  417: 'OutSystems',\n",
       "  418: 'Ovo Energy',\n",
       "  419: 'ParkJockey',\n",
       "  420: 'Pat McGrath Labs',\n",
       "  421: '毒',\n",
       "  422: 'PolicyBazaar',\n",
       "  423: '辉能科技',\n",
       "  424: 'Proteus Digital Health',\n",
       "  425: 'Quikr',\n",
       "  426: 'Raise',\n",
       "  427: 'Rappi',\n",
       "  428: '人人车',\n",
       "  429: '人人贷',\n",
       "  430: 'Rent the Runway',\n",
       "  431: 'Revolution Precrafted',\n",
       "  432: 'Rivigo',\n",
       "  433: 'Rocket Lab',\n",
       "  434: 'Root Insurance',\n",
       "  435: 'Rubicon Global',\n",
       "  436: 'Seismic',\n",
       "  437: 'Shopclues',\n",
       "  438: '首汽约车',\n",
       "  439: '水滴',\n",
       "  440: 'Sila Nanotechnologies',\n",
       "  441: '神州细胞工程',\n",
       "  442: '智米科技',\n",
       "  443: 'Sonder',\n",
       "  444: 'SoundHound',\n",
       "  445: 'StockX',\n",
       "  446: 'Sumo Logic',\n",
       "  447: 'sweetgreen',\n",
       "  448: 'Symphony Communication Services',\n",
       "  449: 'Taboola',\n",
       "  450: 'Talkdesk',\n",
       "  451: '腾云天下',\n",
       "  452: 'Tango',\n",
       "  453: 'TechStyle Fashion Group',\n",
       "  454: '企鹅杏仁',\n",
       "  455: 'The Honest Company',\n",
       "  456: 'ThoughtSpot',\n",
       "  457: 'Thumbtack',\n",
       "  458: 'TMON',\n",
       "  459: 'Toss',\n",
       "  460: 'Tradeshift',\n",
       "  461: 'Tresata',\n",
       "  462: 'Turo',\n",
       "  463: '图森未来',\n",
       "  464: '优刻得',\n",
       "  465: 'Udaan',\n",
       "  466: 'Udacity',\n",
       "  467: '云知声',\n",
       "  468: 'V领地',\n",
       "  469: 'View',\n",
       "  470: 'Vlocity',\n",
       "  471: 'Vox Media',\n",
       "  472: 'VTS',\n",
       "  473: '挖财',\n",
       "  474: 'WalkMe',\n",
       "  475: 'WeLab',\n",
       "  476: '万能钥匙',\n",
       "  477: '我买网',\n",
       "  478: '汇桔网',\n",
       "  479: 'Yanolja',\n",
       "  480: '要出发',\n",
       "  481: '越海全球',\n",
       "  482: '一点资讯',\n",
       "  483: '易久批',\n",
       "  484: '壹米滴答',\n",
       "  485: '洋码头',\n",
       "  486: '有利网',\n",
       "  487: '网易有道',\n",
       "  488: '云鸟科技',\n",
       "  489: 'Zeta Global',\n",
       "  490: '掌门1对1',\n",
       "  491: '转转',\n",
       "  492: 'Zipline International',\n",
       "  493: 'ZipRecruiter'},\n",
       " 'Company Name': {0: 'Ant Financial',\n",
       "  1: 'Bytedance',\n",
       "  2: 'Didi Chuxing',\n",
       "  3: 'Infor',\n",
       "  4: 'JUUL Labs',\n",
       "  5: 'Airbnb',\n",
       "  6: 'Lufax',\n",
       "  7: 'SpaceX',\n",
       "  8: 'WeWork',\n",
       "  9: 'Stripe',\n",
       "  10: 'WeBank',\n",
       "  11: 'Cainiao',\n",
       "  12: 'JD Digits',\n",
       "  13: 'Kuaishou',\n",
       "  14: 'DJI',\n",
       "  15: 'Grab',\n",
       "  16: 'Hulu',\n",
       "  17: 'Palantir Technologies',\n",
       "  18: 'DoorDash',\n",
       "  19: 'Bitmain',\n",
       "  20: 'JD Logistics',\n",
       "  21: 'Samumed',\n",
       "  22: 'GO-JEK',\n",
       "  23: 'Paytm',\n",
       "  24: 'Beike',\n",
       "  25: 'CARS',\n",
       "  26: 'Coupang',\n",
       "  27: 'Ping An Healthcare Technology',\n",
       "  28: 'Wish',\n",
       "  29: 'Coinbase',\n",
       "  30: 'GRAIL',\n",
       "  31: 'Instacart',\n",
       "  32: 'Robinhood',\n",
       "  33: 'Argo AI',\n",
       "  34: 'Meicai',\n",
       "  35: 'OneConnect',\n",
       "  36: 'Roivant Sciences',\n",
       "  37: 'Suning Finance',\n",
       "  38: 'Tanium',\n",
       "  39: 'Tokopedia',\n",
       "  40: 'Uber ATG',\n",
       "  41: 'UiPath',\n",
       "  42: 'BYJU’s',\n",
       "  43: 'Full Truck Alliance',\n",
       "  44: 'Magic Leap',\n",
       "  45: 'Ola Cabs',\n",
       "  46: 'SenseTime',\n",
       "  47: 'UCAR',\n",
       "  48: 'WeDoctor',\n",
       "  49: 'Bluehole',\n",
       "  50: 'Lazada',\n",
       "  51: 'Machine Zone',\n",
       "  52: 'OYO Rooms',\n",
       "  53: 'Ripple',\n",
       "  54: 'Rivian',\n",
       "  55: 'The Hut Group',\n",
       "  56: 'Auto1 Group',\n",
       "  57: 'Compass',\n",
       "  58: 'Credit Karma',\n",
       "  59: 'Faraday Future',\n",
       "  60: 'Houzz',\n",
       "  61: 'Indigo Agriculture',\n",
       "  62: 'Klarna',\n",
       "  63: 'Megvii',\n",
       "  64: 'New Dada',\n",
       "  65: 'Niantic',\n",
       "  66: 'Nubank',\n",
       "  67: 'OpenDoor Labs',\n",
       "  68: 'Peloton',\n",
       "  69: 'Royole',\n",
       "  70: 'Samsara Networks',\n",
       "  71: 'Snowflake Computing',\n",
       "  72: 'SoFi',\n",
       "  73: 'TransferWise',\n",
       "  74: 'Traveloka',\n",
       "  75: 'TripActions',\n",
       "  76: 'Ubtech',\n",
       "  77: 'United Imaging',\n",
       "  78: 'WM Motor',\n",
       "  79: 'Xpeng Motors',\n",
       "  80: 'Ziroom',\n",
       "  81: 'Zomato',\n",
       "  82: 'Greensill',\n",
       "  83: 'Affirm',\n",
       "  84: 'Automation Anywhere',\n",
       "  85: 'Bona film',\n",
       "  86: 'Brex',\n",
       "  87: 'Canaan',\n",
       "  88: 'Canva',\n",
       "  89: 'China UMS',\n",
       "  90: 'Circle Internet Financial',\n",
       "  91: 'Cloudwalk',\n",
       "  92: 'Confluent',\n",
       "  93: 'Dadi Digital Cinema',\n",
       "  94: 'Databricks',\n",
       "  95: 'Douyu',\n",
       "  96: 'Du Xiaoman Financial',\n",
       "  97: 'Flexport',\n",
       "  98: 'GoodRx',\n",
       "  99: 'Hellobike',\n",
       "  100: 'Henlius',\n",
       "  101: 'Himalaya',\n",
       "  102: 'Horizon Robotics',\n",
       "  103: 'Huitongda',\n",
       "  104: 'Katerra',\n",
       "  105: 'Kuayue Express',\n",
       "  106: 'Missfresh',\n",
       "  107: 'Monzo',\n",
       "  108: 'N26',\n",
       "  109: 'Nuro',\n",
       "  110: 'OakNorth',\n",
       "  111: 'OneWeb',\n",
       "  112: 'Oscar Health',\n",
       "  113: 'Paytm Mall',\n",
       "  114: 'Plaid Technologies',\n",
       "  115: 'Procore Technologies',\n",
       "  116: 'Qi An Xin',\n",
       "  117: 'reddit',\n",
       "  118: 'Roblox',\n",
       "  119: 'Rubrik',\n",
       "  120: 'Singulato',\n",
       "  121: 'SmileDirectClub',\n",
       "  122: 'Souche',\n",
       "  123: 'Swiggy',\n",
       "  124: 'Tempus',\n",
       "  125: 'Toast',\n",
       "  126: 'Unity Technologies',\n",
       "  127: 'UrWork',\n",
       "  128: 'VIPKID',\n",
       "  129: 'Woowa Brothers',\n",
       "  130: 'Xiaohongshu',\n",
       "  131: 'Yiguo',\n",
       "  132: 'Yixia',\n",
       "  133: 'Youxia',\n",
       "  134: 'Yuanfudao',\n",
       "  135: 'Zoox',\n",
       "  136: 'Zuoyebang',\n",
       "  137: '23andMe',\n",
       "  138: 'Afiniti',\n",
       "  139: 'Aihuishou',\n",
       "  140: 'AppLovin',\n",
       "  141: 'APUS',\n",
       "  142: 'Asana',\n",
       "  143: 'Aurora',\n",
       "  144: 'Avant',\n",
       "  145: 'BenevolentAI',\n",
       "  146: 'BillDesk',\n",
       "  147: 'Binance',\n",
       "  148: 'Bird Rides',\n",
       "  149: 'BlaBlaCar',\n",
       "  150: 'Block.One',\n",
       "  151: 'Buzzfeed',\n",
       "  152: 'Byton',\n",
       "  153: 'Cambricon',\n",
       "  154: 'Canxing',\n",
       "  155: 'Carbon',\n",
       "  156: 'Carta',\n",
       "  157: 'Checkout.com',\n",
       "  158: 'Chehejia',\n",
       "  159: 'Chime',\n",
       "  160: 'CureVac',\n",
       "  161: 'Darktrace',\n",
       "  162: 'Dataminr',\n",
       "  163: 'Delhivery',\n",
       "  164: 'Deliveroo',\n",
       "  165: 'Desktop Metal',\n",
       "  166: 'Devoted Health',\n",
       "  167: 'Dfinity',\n",
       "  168: 'Discord',\n",
       "  169: 'FlixBus',\n",
       "  170: 'Freshworks',\n",
       "  171: 'Gett',\n",
       "  172: 'Graphcore',\n",
       "  173: 'Gusto',\n",
       "  174: 'HashiCorp',\n",
       "  175: 'HeartFlow',\n",
       "  176: 'Impossible Foods',\n",
       "  177: 'Improbable',\n",
       "  178: 'Infinidat',\n",
       "  179: 'InsideSales.com',\n",
       "  180: 'InVision',\n",
       "  181: 'Jusda',\n",
       "  182: 'Kaseya',\n",
       "  183: 'Kingsoft Cloud',\n",
       "  184: 'Landa Digital Printing',\n",
       "  185: 'Lemonade',\n",
       "  186: 'Lime',\n",
       "  187: 'Mafengwo',\n",
       "  188: 'Marqeta',\n",
       "  189: 'Miniso',\n",
       "  190: 'Monday.com',\n",
       "  191: 'Mozido',\n",
       "  192: 'Mu Sigma',\n",
       "  193: 'NantOmics',\n",
       "  194: 'Nextdoor',\n",
       "  195: 'Njoy',\n",
       "  196: 'Northvolt',\n",
       "  197: 'Oxford Nanopore Technologies',\n",
       "  198: 'PAX',\n",
       "  199: 'PingPong',\n",
       "  200: 'Pony.ai',\n",
       "  201: 'Postmates',\n",
       "  202: 'Preferred Networks',\n",
       "  203: 'Quanergy Systems',\n",
       "  204: 'Quora',\n",
       "  205: 'RELX',\n",
       "  206: 'ReNew Power',\n",
       "  207: 'Revolut',\n",
       "  208: 'Segment',\n",
       "  209: 'ServiceTitan',\n",
       "  210: 'Sharecare',\n",
       "  211: 'Sprinklr',\n",
       "  212: 'Squarespace',\n",
       "  213: 'STX Entertainment',\n",
       "  214: 'Suning Sports',\n",
       "  215: 'Taobao Dianying',\n",
       "  216: 'Uptake',\n",
       "  217: 'Warby Parker',\n",
       "  218: 'YITU',\n",
       "  219: 'Zenefits',\n",
       "  220: 'Zhihu',\n",
       "  221: 'ZocDoc',\n",
       "  222: 'Zume',\n",
       "  223: 'Aiways',\n",
       "  224: 'Caocao',\n",
       "  225: 'Danke',\n",
       "  226: 'Ebang',\n",
       "  227: 'Enovate',\n",
       "  228: 'ETCP',\n",
       "  229: 'Gaodun',\n",
       "  230: 'Hero Entertainment',\n",
       "  231: 'Huimin',\n",
       "  232: 'IMS',\n",
       "  233: 'iSoftstone',\n",
       "  234: 'JD Health',\n",
       "  235: 'Jiemian',\n",
       "  236: 'Kidswant',\n",
       "  237: 'KLOOK',\n",
       "  238: 'lvmama',\n",
       "  239: 'Mia',\n",
       "  240: 'Mofang',\n",
       "  241: 'Moviebook',\n",
       "  242: 'NetEase Music',\n",
       "  243: 'Ninebot',\n",
       "  244: 'Panshi',\n",
       "  245: 'PurCotton',\n",
       "  246: 'RRS',\n",
       "  247: 'SheIn',\n",
       "  248: 'Shuhai',\n",
       "  249: 'Skywell',\n",
       "  250: 'Chindata',\n",
       "  251: 'Tongdun',\n",
       "  252: 'Tubatu',\n",
       "  253: 'Tuhu',\n",
       "  254: 'Tujia',\n",
       "  255: 'TuyaSmart',\n",
       "  256: 'Weidian',\n",
       "  257: 'Whaley',\n",
       "  258: 'WuXi NextCODE',\n",
       "  259: 'xiaozhu',\n",
       "  260: 'Xinchao',\n",
       "  261: 'Zbj',\n",
       "  262: 'Zhaogang',\n",
       "  263: '100credit',\n",
       "  264: '10X Genomics',\n",
       "  265: '17zuoye',\n",
       "  266: '1919 Wines & Spirits',\n",
       "  267: '4paradigm',\n",
       "  268: '9fgroup',\n",
       "  269: 'About You',\n",
       "  270: 'Actifio',\n",
       "  271: 'Age of Learning',\n",
       "  272: 'Airtable',\n",
       "  273: 'Airwallex',\n",
       "  274: 'Akulaku',\n",
       "  275: 'Alisports',\n",
       "  276: 'Allbirds',\n",
       "  277: 'Alphaeon Corporation',\n",
       "  278: 'Ane',\n",
       "  279: 'Ankon',\n",
       "  280: 'AppDirect',\n",
       "  281: 'Auth0',\n",
       "  282: 'Automattic',\n",
       "  283: 'AvidXchange',\n",
       "  284: 'Away',\n",
       "  285: 'Banma',\n",
       "  286: 'Beibei',\n",
       "  287: 'BigBasket',\n",
       "  288: 'Bill.com',\n",
       "  289: 'BitFury',\n",
       "  290: 'Bolt',\n",
       "  291: 'Boqii',\n",
       "  292: 'Bordrin',\n",
       "  293: 'Branch',\n",
       "  294: 'Bukalapak',\n",
       "  295: 'Butterfly Network',\n",
       "  296: 'C3',\n",
       "  297: 'Cabify',\n",
       "  298: 'Calm.com',\n",
       "  299: 'Carzone',\n",
       "  300: 'Casper',\n",
       "  301: 'Celonis',\n",
       "  302: 'ChargePoint',\n",
       "  303: 'Chemao',\n",
       "  304: 'Chezhibao',\n",
       "  305: 'Chunyuyisheng',\n",
       "  306: 'CloudFlare',\n",
       "  307: 'Clover Health',\n",
       "  308: 'Cohesity',\n",
       "  309: 'Collibra',\n",
       "  310: 'Como',\n",
       "  311: 'Convoy',\n",
       "  312: 'Coursera',\n",
       "  313: 'DaDa',\n",
       "  314: 'Daojia',\n",
       "  315: 'DataRobot',\n",
       "  316: 'Dataxu',\n",
       "  317: 'Deezer',\n",
       "  318: 'Dianrong',\n",
       "  319: 'Docker',\n",
       "  320: 'Doctolib',\n",
       "  321: 'DotC United',\n",
       "  322: 'DraftKings',\n",
       "  323: 'Dream11',\n",
       "  324: 'Druva',\n",
       "  325: 'Dtdream',\n",
       "  326: 'Dxy',\n",
       "  327: 'Easy Life',\n",
       "  328: 'Envision',\n",
       "  329: 'Evernote',\n",
       "  330: 'ezCater',\n",
       "  331: 'Fair',\n",
       "  332: 'FangDD',\n",
       "  333: 'Fanli',\n",
       "  334: 'Fcbox',\n",
       "  335: 'Formlabs',\n",
       "  336: 'Fxiaoke',\n",
       "  337: 'G7',\n",
       "  338: 'Geo',\n",
       "  339: 'GetYourGuide',\n",
       "  340: 'Ginkgo BioWorks',\n",
       "  341: 'GitLab',\n",
       "  342: 'Global Fashion Group',\n",
       "  343: 'Glossier',\n",
       "  344: 'Gympass',\n",
       "  345: 'Haodf',\n",
       "  346: 'Health Catalyst',\n",
       "  347: 'Hike',\n",
       "  348: 'Hims',\n",
       "  349: 'HMD',\n",
       "  350: 'Hosjoy',\n",
       "  351: 'Hozon',\n",
       "  352: 'Huayun',\n",
       "  353: 'Huikedu Group',\n",
       "  354: 'Hujiang',\n",
       "  355: 'Human Longevity',\n",
       "  356: 'Icarbonx',\n",
       "  357: 'Icertis',\n",
       "  358: 'iFood',\n",
       "  359: 'Ihomefnt',\n",
       "  360: 'Illumio',\n",
       "  361: 'InMobi',\n",
       "  362: 'Intercom',\n",
       "  363: 'Ipien',\n",
       "  364: 'ironSource',\n",
       "  365: 'iTutorGroup',\n",
       "  366: 'Ivalua',\n",
       "  367: 'JFrog',\n",
       "  368: 'JiuXian',\n",
       "  369: 'Jollycorp',\n",
       "  370: 'Juanpi',\n",
       "  371: 'Juma',\n",
       "  372: 'Jusfoun',\n",
       "  373: 'Kabbage',\n",
       "  374: 'KeepTruckin',\n",
       "  375: 'Kendra Scott',\n",
       "  376: 'KnowBe4',\n",
       "  377: 'Knowbox',\n",
       "  378: 'Kr Space',\n",
       "  379: 'Lalamove',\n",
       "  380: 'Lamabang',\n",
       "  381: 'Leapmotor',\n",
       "  382: 'letgo',\n",
       "  383: 'Lianlian',\n",
       "  384: 'Lightricks',\n",
       "  385: 'Linkdoc',\n",
       "  386: 'Linklogis',\n",
       "  387: 'Linmon',\n",
       "  388: 'Liquid Global',\n",
       "  389: 'Loggi',\n",
       "  390: 'Loji',\n",
       "  391: 'Lookout',\n",
       "  392: 'Luojilab',\n",
       "  393: 'Maimai',\n",
       "  394: 'MarkLogic',\n",
       "  395: 'MediaMath',\n",
       "  396: 'Meero',\n",
       "  397: 'Mesosphere',\n",
       "  398: 'Miaoshou',\n",
       "  399: 'Microvast',\n",
       "  400: 'MindMaze',\n",
       "  401: 'Mininglamp',\n",
       "  402: 'Mobvoi',\n",
       "  403: 'Momenta',\n",
       "  404: 'MoneyLion',\n",
       "  405: 'Netskope',\n",
       "  406: 'Nikola Motor Company',\n",
       "  407: 'Nome',\n",
       "  408: 'Novogene',\n",
       "  409: 'OfferUp',\n",
       "  410: 'Ola Electric',\n",
       "  411: 'Omio',\n",
       "  412: 'One Medical Group',\n",
       "  413: 'OneTrust',\n",
       "  414: 'Orbbec',\n",
       "  415: 'OrCam Technologies',\n",
       "  416: 'Outreach',\n",
       "  417: 'OutSystems',\n",
       "  418: 'Ovo Energy',\n",
       "  419: 'ParkJockey',\n",
       "  420: 'Pat McGrath Labs',\n",
       "  421: 'Poizon',\n",
       "  422: 'PolicyBazaar',\n",
       "  423: 'Prologium',\n",
       "  424: 'Proteus Digital Health',\n",
       "  425: 'Quikr',\n",
       "  426: 'Raise',\n",
       "  427: 'Rappi',\n",
       "  428: 'Renrenche',\n",
       "  429: 'Renrendai',\n",
       "  430: 'Rent the Runway',\n",
       "  431: 'Revolution Precrafted',\n",
       "  432: 'Rivigo',\n",
       "  433: 'Rocket Lab',\n",
       "  434: 'Root Insurance',\n",
       "  435: 'Rubicon Global',\n",
       "  436: 'Seismic',\n",
       "  437: 'Shopclues',\n",
       "  438: 'Shouqi',\n",
       "  439: 'Shuidi',\n",
       "  440: 'Sila Nanotechnologies',\n",
       "  441: 'Sinocelltech',\n",
       "  442: 'Smartmi',\n",
       "  443: 'Sonder',\n",
       "  444: 'SoundHound',\n",
       "  445: 'StockX',\n",
       "  446: 'Sumo Logic',\n",
       "  447: 'sweetgreen',\n",
       "  448: 'Symphony Communication Services',\n",
       "  449: 'Taboola',\n",
       "  450: 'Talkdesk',\n",
       "  451: 'TalkingData',\n",
       "  452: 'Tango',\n",
       "  453: 'TechStyle Fashion Group',\n",
       "  454: 'Tencent Trusted Doctors',\n",
       "  455: 'The Honest Company',\n",
       "  456: 'ThoughtSpot',\n",
       "  457: 'Thumbtack',\n",
       "  458: 'TMON',\n",
       "  459: 'Toss',\n",
       "  460: 'Tradeshift',\n",
       "  461: 'Tresata',\n",
       "  462: 'Turo',\n",
       "  463: 'TuSimple',\n",
       "  464: 'UCloud',\n",
       "  465: 'Udaan',\n",
       "  466: 'Udacity',\n",
       "  467: 'Unisound',\n",
       "  468: 'V Linker',\n",
       "  469: 'View',\n",
       "  470: 'Vlocity',\n",
       "  471: 'Vox Media',\n",
       "  472: 'VTS',\n",
       "  473: 'Wacai',\n",
       "  474: 'WalkMe',\n",
       "  475: 'WeLab',\n",
       "  476: 'WiFi Master key',\n",
       "  477: 'Womai',\n",
       "  478: 'WTOIP',\n",
       "  479: 'Yanolja',\n",
       "  480: 'Yaochufa',\n",
       "  481: 'YH Global',\n",
       "  482: 'Yidianzixun',\n",
       "  483: 'Yijiupi',\n",
       "  484: 'Yimidida',\n",
       "  485: 'yMatou',\n",
       "  486: 'Yooli',\n",
       "  487: 'Youdao',\n",
       "  488: 'Yunniao',\n",
       "  489: 'Zeta Global',\n",
       "  490: 'Zhangmen',\n",
       "  491: 'Zhuanzhuan',\n",
       "  492: 'Zipline International',\n",
       "  493: 'ZipRecruiter'},\n",
       " '估值（亿人民币）': {0: 10000,\n",
       "  1: 5000,\n",
       "  2: 3600,\n",
       "  3: 3500,\n",
       "  4: 3400,\n",
       "  5: 2700,\n",
       "  6: 2700,\n",
       "  7: 2500,\n",
       "  8: 2100,\n",
       "  9: 1600,\n",
       "  10: 1500,\n",
       "  11: 1300,\n",
       "  12: 1300,\n",
       "  13: 1200,\n",
       "  14: 1000,\n",
       "  15: 1000,\n",
       "  16: 1000,\n",
       "  17: 1000,\n",
       "  18: 900,\n",
       "  19: 800,\n",
       "  20: 800,\n",
       "  21: 800,\n",
       "  22: 700,\n",
       "  23: 700,\n",
       "  24: 600,\n",
       "  25: 600,\n",
       "  26: 600,\n",
       "  27: 600,\n",
       "  28: 600,\n",
       "  29: 550,\n",
       "  30: 550,\n",
       "  31: 550,\n",
       "  32: 550,\n",
       "  33: 500,\n",
       "  34: 500,\n",
       "  35: 500,\n",
       "  36: 500,\n",
       "  37: 500,\n",
       "  38: 500,\n",
       "  39: 500,\n",
       "  40: 500,\n",
       "  41: 500,\n",
       "  42: 400,\n",
       "  43: 400,\n",
       "  44: 400,\n",
       "  45: 400,\n",
       "  46: 400,\n",
       "  47: 400,\n",
       "  48: 400,\n",
       "  49: 350,\n",
       "  50: 350,\n",
       "  51: 350,\n",
       "  52: 350,\n",
       "  53: 350,\n",
       "  54: 350,\n",
       "  55: 350,\n",
       "  56: 300,\n",
       "  57: 300,\n",
       "  58: 300,\n",
       "  59: 300,\n",
       "  60: 300,\n",
       "  61: 300,\n",
       "  62: 300,\n",
       "  63: 300,\n",
       "  64: 300,\n",
       "  65: 300,\n",
       "  66: 300,\n",
       "  67: 300,\n",
       "  68: 300,\n",
       "  69: 300,\n",
       "  70: 300,\n",
       "  71: 300,\n",
       "  72: 300,\n",
       "  73: 300,\n",
       "  74: 300,\n",
       "  75: 300,\n",
       "  76: 300,\n",
       "  77: 300,\n",
       "  78: 300,\n",
       "  79: 300,\n",
       "  80: 300,\n",
       "  81: 300,\n",
       "  82: 250,\n",
       "  83: 200,\n",
       "  84: 200,\n",
       "  85: 200,\n",
       "  86: 200,\n",
       "  87: 200,\n",
       "  88: 200,\n",
       "  89: 200,\n",
       "  90: 200,\n",
       "  91: 200,\n",
       "  92: 200,\n",
       "  93: 200,\n",
       "  94: 200,\n",
       "  95: 200,\n",
       "  96: 200,\n",
       "  97: 200,\n",
       "  98: 200,\n",
       "  99: 200,\n",
       "  100: 200,\n",
       "  101: 200,\n",
       "  102: 200,\n",
       "  103: 200,\n",
       "  104: 200,\n",
       "  105: 200,\n",
       "  106: 200,\n",
       "  107: 200,\n",
       "  108: 200,\n",
       "  109: 200,\n",
       "  110: 200,\n",
       "  111: 200,\n",
       "  112: 200,\n",
       "  113: 200,\n",
       "  114: 200,\n",
       "  115: 200,\n",
       "  116: 200,\n",
       "  117: 200,\n",
       "  118: 200,\n",
       "  119: 200,\n",
       "  120: 200,\n",
       "  121: 200,\n",
       "  122: 200,\n",
       "  123: 200,\n",
       "  124: 200,\n",
       "  125: 200,\n",
       "  126: 200,\n",
       "  127: 200,\n",
       "  128: 200,\n",
       "  129: 200,\n",
       "  130: 200,\n",
       "  131: 200,\n",
       "  132: 200,\n",
       "  133: 200,\n",
       "  134: 200,\n",
       "  135: 200,\n",
       "  136: 200,\n",
       "  137: 150,\n",
       "  138: 150,\n",
       "  139: 150,\n",
       "  140: 150,\n",
       "  141: 150,\n",
       "  142: 150,\n",
       "  143: 150,\n",
       "  144: 150,\n",
       "  145: 150,\n",
       "  146: 150,\n",
       "  147: 150,\n",
       "  148: 150,\n",
       "  149: 150,\n",
       "  150: 150,\n",
       "  151: 150,\n",
       "  152: 150,\n",
       "  153: 150,\n",
       "  154: 150,\n",
       "  155: 150,\n",
       "  156: 150,\n",
       "  157: 150,\n",
       "  158: 150,\n",
       "  159: 150,\n",
       "  160: 150,\n",
       "  161: 150,\n",
       "  162: 150,\n",
       "  163: 150,\n",
       "  164: 150,\n",
       "  165: 150,\n",
       "  166: 150,\n",
       "  167: 150,\n",
       "  168: 150,\n",
       "  169: 150,\n",
       "  170: 150,\n",
       "  171: 150,\n",
       "  172: 150,\n",
       "  173: 150,\n",
       "  174: 150,\n",
       "  175: 150,\n",
       "  176: 150,\n",
       "  177: 150,\n",
       "  178: 150,\n",
       "  179: 150,\n",
       "  180: 150,\n",
       "  181: 150,\n",
       "  182: 150,\n",
       "  183: 150,\n",
       "  184: 150,\n",
       "  185: 150,\n",
       "  186: 150,\n",
       "  187: 150,\n",
       "  188: 150,\n",
       "  189: 150,\n",
       "  190: 150,\n",
       "  191: 150,\n",
       "  192: 150,\n",
       "  193: 150,\n",
       "  194: 150,\n",
       "  195: 150,\n",
       "  196: 150,\n",
       "  197: 150,\n",
       "  198: 150,\n",
       "  199: 150,\n",
       "  200: 150,\n",
       "  201: 150,\n",
       "  202: 150,\n",
       "  203: 150,\n",
       "  204: 150,\n",
       "  205: 150,\n",
       "  206: 150,\n",
       "  207: 150,\n",
       "  208: 150,\n",
       "  209: 150,\n",
       "  210: 150,\n",
       "  211: 150,\n",
       "  212: 150,\n",
       "  213: 150,\n",
       "  214: 150,\n",
       "  215: 150,\n",
       "  216: 150,\n",
       "  217: 150,\n",
       "  218: 150,\n",
       "  219: 150,\n",
       "  220: 150,\n",
       "  221: 150,\n",
       "  222: 150,\n",
       "  223: 100,\n",
       "  224: 100,\n",
       "  225: 100,\n",
       "  226: 100,\n",
       "  227: 100,\n",
       "  228: 100,\n",
       "  229: 100,\n",
       "  230: 100,\n",
       "  231: 100,\n",
       "  232: 100,\n",
       "  233: 100,\n",
       "  234: 100,\n",
       "  235: 100,\n",
       "  236: 100,\n",
       "  237: 100,\n",
       "  238: 100,\n",
       "  239: 100,\n",
       "  240: 100,\n",
       "  241: 100,\n",
       "  242: 100,\n",
       "  243: 100,\n",
       "  244: 100,\n",
       "  245: 100,\n",
       "  246: 100,\n",
       "  247: 100,\n",
       "  248: 100,\n",
       "  249: 100,\n",
       "  250: 100,\n",
       "  251: 100,\n",
       "  252: 100,\n",
       "  253: 100,\n",
       "  254: 100,\n",
       "  255: 100,\n",
       "  256: 100,\n",
       "  257: 100,\n",
       "  258: 100,\n",
       "  259: 100,\n",
       "  260: 100,\n",
       "  261: 100,\n",
       "  262: 100,\n",
       "  263: 70,\n",
       "  264: 70,\n",
       "  265: 70,\n",
       "  266: 70,\n",
       "  267: 70,\n",
       "  268: 70,\n",
       "  269: 70,\n",
       "  270: 70,\n",
       "  271: 70,\n",
       "  272: 70,\n",
       "  273: 70,\n",
       "  274: 70,\n",
       "  275: 70,\n",
       "  276: 70,\n",
       "  277: 70,\n",
       "  278: 70,\n",
       "  279: 70,\n",
       "  280: 70,\n",
       "  281: 70,\n",
       "  282: 70,\n",
       "  283: 70,\n",
       "  284: 70,\n",
       "  285: 70,\n",
       "  286: 70,\n",
       "  287: 70,\n",
       "  288: 70,\n",
       "  289: 70,\n",
       "  290: 70,\n",
       "  291: 70,\n",
       "  292: 70,\n",
       "  293: 70,\n",
       "  294: 70,\n",
       "  295: 70,\n",
       "  296: 70,\n",
       "  297: 70,\n",
       "  298: 70,\n",
       "  299: 70,\n",
       "  300: 70,\n",
       "  301: 70,\n",
       "  302: 70,\n",
       "  303: 70,\n",
       "  304: 70,\n",
       "  305: 70,\n",
       "  306: 70,\n",
       "  307: 70,\n",
       "  308: 70,\n",
       "  309: 70,\n",
       "  310: 70,\n",
       "  311: 70,\n",
       "  312: 70,\n",
       "  313: 70,\n",
       "  314: 70,\n",
       "  315: 70,\n",
       "  316: 70,\n",
       "  317: 70,\n",
       "  318: 70,\n",
       "  319: 70,\n",
       "  320: 70,\n",
       "  321: 70,\n",
       "  322: 70,\n",
       "  323: 70,\n",
       "  324: 70,\n",
       "  325: 70,\n",
       "  326: 70,\n",
       "  327: 70,\n",
       "  328: 70,\n",
       "  329: 70,\n",
       "  330: 70,\n",
       "  331: 70,\n",
       "  332: 70,\n",
       "  333: 70,\n",
       "  334: 70,\n",
       "  335: 70,\n",
       "  336: 70,\n",
       "  337: 70,\n",
       "  338: 70,\n",
       "  339: 70,\n",
       "  340: 70,\n",
       "  341: 70,\n",
       "  342: 70,\n",
       "  343: 70,\n",
       "  344: 70,\n",
       "  345: 70,\n",
       "  346: 70,\n",
       "  347: 70,\n",
       "  348: 70,\n",
       "  349: 70,\n",
       "  350: 70,\n",
       "  351: 70,\n",
       "  352: 70,\n",
       "  353: 70,\n",
       "  354: 70,\n",
       "  355: 70,\n",
       "  356: 70,\n",
       "  357: 70,\n",
       "  358: 70,\n",
       "  359: 70,\n",
       "  360: 70,\n",
       "  361: 70,\n",
       "  362: 70,\n",
       "  363: 70,\n",
       "  364: 70,\n",
       "  365: 70,\n",
       "  366: 70,\n",
       "  367: 70,\n",
       "  368: 70,\n",
       "  369: 70,\n",
       "  370: 70,\n",
       "  371: 70,\n",
       "  372: 70,\n",
       "  373: 70,\n",
       "  374: 70,\n",
       "  375: 70,\n",
       "  376: 70,\n",
       "  377: 70,\n",
       "  378: 70,\n",
       "  379: 70,\n",
       "  380: 70,\n",
       "  381: 70,\n",
       "  382: 70,\n",
       "  383: 70,\n",
       "  384: 70,\n",
       "  385: 70,\n",
       "  386: 70,\n",
       "  387: 70,\n",
       "  388: 70,\n",
       "  389: 70,\n",
       "  390: 70,\n",
       "  391: 70,\n",
       "  392: 70,\n",
       "  393: 70,\n",
       "  394: 70,\n",
       "  395: 70,\n",
       "  396: 70,\n",
       "  397: 70,\n",
       "  398: 70,\n",
       "  399: 70,\n",
       "  400: 70,\n",
       "  401: 70,\n",
       "  402: 70,\n",
       "  403: 70,\n",
       "  404: 70,\n",
       "  405: 70,\n",
       "  406: 70,\n",
       "  407: 70,\n",
       "  408: 70,\n",
       "  409: 70,\n",
       "  410: 70,\n",
       "  411: 70,\n",
       "  412: 70,\n",
       "  413: 70,\n",
       "  414: 70,\n",
       "  415: 70,\n",
       "  416: 70,\n",
       "  417: 70,\n",
       "  418: 70,\n",
       "  419: 70,\n",
       "  420: 70,\n",
       "  421: 70,\n",
       "  422: 70,\n",
       "  423: 70,\n",
       "  424: 70,\n",
       "  425: 70,\n",
       "  426: 70,\n",
       "  427: 70,\n",
       "  428: 70,\n",
       "  429: 70,\n",
       "  430: 70,\n",
       "  431: 70,\n",
       "  432: 70,\n",
       "  433: 70,\n",
       "  434: 70,\n",
       "  435: 70,\n",
       "  436: 70,\n",
       "  437: 70,\n",
       "  438: 70,\n",
       "  439: 70,\n",
       "  440: 70,\n",
       "  441: 70,\n",
       "  442: 70,\n",
       "  443: 70,\n",
       "  444: 70,\n",
       "  445: 70,\n",
       "  446: 70,\n",
       "  447: 70,\n",
       "  448: 70,\n",
       "  449: 70,\n",
       "  450: 70,\n",
       "  451: 70,\n",
       "  452: 70,\n",
       "  453: 70,\n",
       "  454: 70,\n",
       "  455: 70,\n",
       "  456: 70,\n",
       "  457: 70,\n",
       "  458: 70,\n",
       "  459: 70,\n",
       "  460: 70,\n",
       "  461: 70,\n",
       "  462: 70,\n",
       "  463: 70,\n",
       "  464: 70,\n",
       "  465: 70,\n",
       "  466: 70,\n",
       "  467: 70,\n",
       "  468: 70,\n",
       "  469: 70,\n",
       "  470: 70,\n",
       "  471: 70,\n",
       "  472: 70,\n",
       "  473: 70,\n",
       "  474: 70,\n",
       "  475: 70,\n",
       "  476: 70,\n",
       "  477: 70,\n",
       "  478: 70,\n",
       "  479: 70,\n",
       "  480: 70,\n",
       "  481: 70,\n",
       "  482: 70,\n",
       "  483: 70,\n",
       "  484: 70,\n",
       "  485: 70,\n",
       "  486: 70,\n",
       "  487: 70,\n",
       "  488: 70,\n",
       "  489: 70,\n",
       "  490: 70,\n",
       "  491: 70,\n",
       "  492: 70,\n",
       "  493: 70},\n",
       " '国家': {0: '中国',\n",
       "  1: '中国',\n",
       "  2: '中国',\n",
       "  3: '美国',\n",
       "  4: '美国',\n",
       "  5: '美国',\n",
       "  6: '中国',\n",
       "  7: '美国',\n",
       "  8: '美国',\n",
       "  9: '美国',\n",
       "  10: '中国',\n",
       "  11: '中国',\n",
       "  12: '中国',\n",
       "  13: '中国',\n",
       "  14: '中国',\n",
       "  15: '新加坡',\n",
       "  16: '美国',\n",
       "  17: '美国',\n",
       "  18: '美国',\n",
       "  19: '中国',\n",
       "  20: '中国',\n",
       "  21: '美国',\n",
       "  22: '印度尼西亚',\n",
       "  23: '印度',\n",
       "  24: '中国',\n",
       "  25: '中国',\n",
       "  26: '韩国',\n",
       "  27: '中国',\n",
       "  28: '美国',\n",
       "  29: '美国',\n",
       "  30: '美国',\n",
       "  31: '美国',\n",
       "  32: '美国',\n",
       "  33: '美国',\n",
       "  34: '中国',\n",
       "  35: '中国',\n",
       "  36: '瑞士',\n",
       "  37: '中国',\n",
       "  38: '美国',\n",
       "  39: '印度尼西亚',\n",
       "  40: '美国',\n",
       "  41: '美国',\n",
       "  42: '印度',\n",
       "  43: '中国',\n",
       "  44: '美国',\n",
       "  45: '印度',\n",
       "  46: '中国',\n",
       "  47: '中国',\n",
       "  48: '中国',\n",
       "  49: '韩国',\n",
       "  50: '新加坡',\n",
       "  51: '美国',\n",
       "  52: '印度',\n",
       "  53: '美国',\n",
       "  54: '美国',\n",
       "  55: '英国',\n",
       "  56: '德国',\n",
       "  57: '美国',\n",
       "  58: '美国',\n",
       "  59: '美国',\n",
       "  60: '美国',\n",
       "  61: '美国',\n",
       "  62: '瑞典',\n",
       "  63: '中国',\n",
       "  64: '中国',\n",
       "  65: '美国',\n",
       "  66: '巴西',\n",
       "  67: '美国',\n",
       "  68: '美国',\n",
       "  69: '中国',\n",
       "  70: '美国',\n",
       "  71: '美国',\n",
       "  72: '美国',\n",
       "  73: '英国',\n",
       "  74: '印度尼西亚',\n",
       "  75: '美国',\n",
       "  76: '中国',\n",
       "  77: '中国',\n",
       "  78: '中国',\n",
       "  79: '中国',\n",
       "  80: '中国',\n",
       "  81: '印度',\n",
       "  82: '英国',\n",
       "  83: '美国',\n",
       "  84: '美国',\n",
       "  85: '中国',\n",
       "  86: '美国',\n",
       "  87: '中国',\n",
       "  88: '澳大利亚',\n",
       "  89: '中国',\n",
       "  90: '美国',\n",
       "  91: '中国',\n",
       "  92: '美国',\n",
       "  93: '中国',\n",
       "  94: '美国',\n",
       "  95: '中国',\n",
       "  96: '中国',\n",
       "  97: '美国',\n",
       "  98: '美国',\n",
       "  99: '中国',\n",
       "  100: '中国',\n",
       "  101: '中国',\n",
       "  102: '中国',\n",
       "  103: '中国',\n",
       "  104: '美国',\n",
       "  105: '中国',\n",
       "  106: '中国',\n",
       "  107: '英国',\n",
       "  108: '德国',\n",
       "  109: '美国',\n",
       "  110: '英国',\n",
       "  111: '美国',\n",
       "  112: '美国',\n",
       "  113: '印度',\n",
       "  114: '美国',\n",
       "  115: '美国',\n",
       "  116: '中国',\n",
       "  117: '美国',\n",
       "  118: '美国',\n",
       "  119: '美国',\n",
       "  120: '中国',\n",
       "  121: '美国',\n",
       "  122: '中国',\n",
       "  123: '印度',\n",
       "  124: '美国',\n",
       "  125: '美国',\n",
       "  126: '美国',\n",
       "  127: '中国',\n",
       "  128: '中国',\n",
       "  129: '韩国',\n",
       "  130: '中国',\n",
       "  131: '中国',\n",
       "  132: '中国',\n",
       "  133: '中国',\n",
       "  134: '中国',\n",
       "  135: '美国',\n",
       "  136: '中国',\n",
       "  137: '美国',\n",
       "  138: '美国',\n",
       "  139: '中国',\n",
       "  140: '美国',\n",
       "  141: '中国',\n",
       "  142: '美国',\n",
       "  143: '美国',\n",
       "  144: '美国',\n",
       "  145: '英国',\n",
       "  146: '印度',\n",
       "  147: '马耳他',\n",
       "  148: '美国',\n",
       "  149: '法国',\n",
       "  150: '中国',\n",
       "  151: '美国',\n",
       "  152: '中国',\n",
       "  153: '中国',\n",
       "  154: '中国',\n",
       "  155: '美国',\n",
       "  156: '美国',\n",
       "  157: '英国',\n",
       "  158: '中国',\n",
       "  159: '美国',\n",
       "  160: '德国',\n",
       "  161: '美国',\n",
       "  162: '美国',\n",
       "  163: '印度',\n",
       "  164: '英国',\n",
       "  165: '美国',\n",
       "  166: '美国',\n",
       "  167: '瑞士',\n",
       "  168: '美国',\n",
       "  169: '德国',\n",
       "  170: '美国',\n",
       "  171: '美国',\n",
       "  172: '英国',\n",
       "  173: '美国',\n",
       "  174: '美国',\n",
       "  175: '美国',\n",
       "  176: '美国',\n",
       "  177: '英国',\n",
       "  178: '以色列',\n",
       "  179: '美国',\n",
       "  180: '美国',\n",
       "  181: '中国',\n",
       "  182: '爱尔兰',\n",
       "  183: '中国',\n",
       "  184: '以色列',\n",
       "  185: '美国',\n",
       "  186: '美国',\n",
       "  187: '中国',\n",
       "  188: '美国',\n",
       "  189: '中国',\n",
       "  190: '以色列',\n",
       "  191: '美国',\n",
       "  192: '印度',\n",
       "  193: '美国',\n",
       "  194: '美国',\n",
       "  195: '美国',\n",
       "  196: '瑞典',\n",
       "  197: '英国',\n",
       "  198: '美国',\n",
       "  199: '中国',\n",
       "  200: '美国',\n",
       "  201: '美国',\n",
       "  202: '日本',\n",
       "  203: '美国',\n",
       "  204: '美国',\n",
       "  205: '中国',\n",
       "  206: '印度',\n",
       "  207: '英国',\n",
       "  208: '美国',\n",
       "  209: '美国',\n",
       "  210: '美国',\n",
       "  211: '美国',\n",
       "  212: '美国',\n",
       "  213: '美国',\n",
       "  214: '中国',\n",
       "  215: '中国',\n",
       "  216: '美国',\n",
       "  217: '美国',\n",
       "  218: '中国',\n",
       "  219: '美国',\n",
       "  220: '中国',\n",
       "  221: '美国',\n",
       "  222: '美国',\n",
       "  223: '中国',\n",
       "  224: '中国',\n",
       "  225: '中国',\n",
       "  226: '中国',\n",
       "  227: '中国',\n",
       "  228: '中国',\n",
       "  229: '中国',\n",
       "  230: '中国',\n",
       "  231: '中国',\n",
       "  232: '中国',\n",
       "  233: '中国',\n",
       "  234: '中国',\n",
       "  235: '中国',\n",
       "  236: '中国',\n",
       "  237: '中国',\n",
       "  238: '中国',\n",
       "  239: '中国',\n",
       "  240: '中国',\n",
       "  241: '中国',\n",
       "  242: '中国',\n",
       "  243: '中国',\n",
       "  244: '中国',\n",
       "  245: '中国',\n",
       "  246: '中国',\n",
       "  247: '中国',\n",
       "  248: '中国',\n",
       "  249: '中国',\n",
       "  250: '中国',\n",
       "  251: '中国',\n",
       "  252: '中国',\n",
       "  253: '中国',\n",
       "  254: '中国',\n",
       "  255: '中国',\n",
       "  256: '中国',\n",
       "  257: '中国',\n",
       "  258: '中国',\n",
       "  259: '中国',\n",
       "  260: '中国',\n",
       "  261: '中国',\n",
       "  262: '中国',\n",
       "  263: '中国',\n",
       "  264: '美国',\n",
       "  265: '中国',\n",
       "  266: '中国',\n",
       "  267: '中国',\n",
       "  268: '中国',\n",
       "  269: '德国',\n",
       "  270: '美国',\n",
       "  271: '美国',\n",
       "  272: '美国',\n",
       "  273: '中国',\n",
       "  274: '中国',\n",
       "  275: '中国',\n",
       "  276: '美国',\n",
       "  277: '美国',\n",
       "  278: '中国',\n",
       "  279: '中国',\n",
       "  280: '美国',\n",
       "  281: '阿根廷',\n",
       "  282: '美国',\n",
       "  283: '美国',\n",
       "  284: '美国',\n",
       "  285: '中国',\n",
       "  286: '中国',\n",
       "  287: '印度',\n",
       "  288: '美国',\n",
       "  289: '美国',\n",
       "  290: '爱沙尼亚',\n",
       "  291: '中国',\n",
       "  292: '中国',\n",
       "  293: '美国',\n",
       "  294: '印度尼西亚',\n",
       "  295: '美国',\n",
       "  296: '美国',\n",
       "  297: '西班牙',\n",
       "  298: '美国',\n",
       "  299: '中国',\n",
       "  300: '美国',\n",
       "  301: '美国',\n",
       "  302: '美国',\n",
       "  303: '中国',\n",
       "  304: '中国',\n",
       "  305: '中国',\n",
       "  306: '美国',\n",
       "  307: '美国',\n",
       "  308: '美国',\n",
       "  309: '美国',\n",
       "  310: '以色列',\n",
       "  311: '美国',\n",
       "  312: '美国',\n",
       "  313: '中国',\n",
       "  314: '中国',\n",
       "  315: '美国',\n",
       "  316: '美国',\n",
       "  317: '法国',\n",
       "  318: '中国',\n",
       "  319: '美国',\n",
       "  320: '法国',\n",
       "  321: '中国',\n",
       "  322: '美国',\n",
       "  323: '印度',\n",
       "  324: '美国',\n",
       "  325: '中国',\n",
       "  326: '中国',\n",
       "  327: '中国',\n",
       "  328: '中国',\n",
       "  329: '美国',\n",
       "  330: '美国',\n",
       "  331: '美国',\n",
       "  332: '中国',\n",
       "  333: '中国',\n",
       "  334: '中国',\n",
       "  335: '美国',\n",
       "  336: '中国',\n",
       "  337: '中国',\n",
       "  338: '中国',\n",
       "  339: '德国',\n",
       "  340: '美国',\n",
       "  341: '美国',\n",
       "  342: '卢森堡',\n",
       "  343: '美国',\n",
       "  344: '巴西',\n",
       "  345: '中国',\n",
       "  346: '美国',\n",
       "  347: '印度',\n",
       "  348: '美国',\n",
       "  349: '芬兰',\n",
       "  350: '中国',\n",
       "  351: '中国',\n",
       "  352: '中国',\n",
       "  353: '中国',\n",
       "  354: '中国',\n",
       "  355: '美国',\n",
       "  356: '中国',\n",
       "  357: '美国',\n",
       "  358: '巴西',\n",
       "  359: '中国',\n",
       "  360: '美国',\n",
       "  361: '印度',\n",
       "  362: '美国',\n",
       "  363: '中国',\n",
       "  364: '以色列',\n",
       "  365: '中国',\n",
       "  366: '美国',\n",
       "  367: '美国',\n",
       "  368: '中国',\n",
       "  369: '中国',\n",
       "  370: '中国',\n",
       "  371: '中国',\n",
       "  372: '中国',\n",
       "  373: '美国',\n",
       "  374: '美国',\n",
       "  375: '美国',\n",
       "  376: '美国',\n",
       "  377: '中国',\n",
       "  378: '中国',\n",
       "  379: '中国',\n",
       "  380: '中国',\n",
       "  381: '中国',\n",
       "  382: '美国',\n",
       "  383: '中国',\n",
       "  384: '以色列',\n",
       "  385: '中国',\n",
       "  386: '中国',\n",
       "  387: '中国',\n",
       "  388: '日本',\n",
       "  389: '巴西',\n",
       "  390: '中国',\n",
       "  391: '美国',\n",
       "  392: '中国',\n",
       "  393: '中国',\n",
       "  394: '美国',\n",
       "  395: '美国',\n",
       "  396: '法国',\n",
       "  397: '美国',\n",
       "  398: '中国',\n",
       "  399: '美国',\n",
       "  400: '瑞士',\n",
       "  401: '中国',\n",
       "  402: '中国',\n",
       "  403: '中国',\n",
       "  404: '美国',\n",
       "  405: '美国',\n",
       "  406: '美国',\n",
       "  407: '中国',\n",
       "  408: '中国',\n",
       "  409: '美国',\n",
       "  410: '印度',\n",
       "  411: '德国',\n",
       "  412: '美国',\n",
       "  413: '美国',\n",
       "  414: '中国',\n",
       "  415: '以色列',\n",
       "  416: '美国',\n",
       "  417: '美国',\n",
       "  418: '英国',\n",
       "  419: '美国',\n",
       "  420: '美国',\n",
       "  421: '中国',\n",
       "  422: '印度',\n",
       "  423: '中国',\n",
       "  424: '美国',\n",
       "  425: '印度',\n",
       "  426: '美国',\n",
       "  427: '哥伦比亚',\n",
       "  428: '中国',\n",
       "  429: '中国',\n",
       "  430: '美国',\n",
       "  431: '菲律宾',\n",
       "  432: '印度',\n",
       "  433: '美国',\n",
       "  434: '美国',\n",
       "  435: '美国',\n",
       "  436: '美国',\n",
       "  437: '印度',\n",
       "  438: '中国',\n",
       "  439: '中国',\n",
       "  440: '美国',\n",
       "  441: '中国',\n",
       "  442: '中国',\n",
       "  443: '美国',\n",
       "  444: '美国',\n",
       "  445: '美国',\n",
       "  446: '美国',\n",
       "  447: '美国',\n",
       "  448: '美国',\n",
       "  449: '美国',\n",
       "  450: '美国',\n",
       "  451: '中国',\n",
       "  452: '美国',\n",
       "  453: '美国',\n",
       "  454: '中国',\n",
       "  455: '美国',\n",
       "  456: '美国',\n",
       "  457: '美国',\n",
       "  458: '韩国',\n",
       "  459: '韩国',\n",
       "  460: '美国',\n",
       "  461: '美国',\n",
       "  462: '美国',\n",
       "  463: '美国',\n",
       "  464: '中国',\n",
       "  465: '印度',\n",
       "  466: '美国',\n",
       "  467: '中国',\n",
       "  468: '中国',\n",
       "  469: '美国',\n",
       "  470: '美国',\n",
       "  471: '美国',\n",
       "  472: '美国',\n",
       "  473: '中国',\n",
       "  474: '美国',\n",
       "  475: '中国',\n",
       "  476: '中国',\n",
       "  477: '中国',\n",
       "  478: '中国',\n",
       "  479: '韩国',\n",
       "  480: '中国',\n",
       "  481: '中国',\n",
       "  482: '中国',\n",
       "  483: '中国',\n",
       "  484: '中国',\n",
       "  485: '中国',\n",
       "  486: '中国',\n",
       "  487: '中国',\n",
       "  488: '中国',\n",
       "  489: '美国',\n",
       "  490: '中国',\n",
       "  491: '中国',\n",
       "  492: '美国',\n",
       "  493: '美国'},\n",
       " '城市': {0: '杭州',\n",
       "  1: '北京',\n",
       "  2: '北京',\n",
       "  3: '纽约',\n",
       "  4: '旧金山',\n",
       "  5: '旧金山',\n",
       "  6: '上海',\n",
       "  7: '洛杉矶',\n",
       "  8: '纽约',\n",
       "  9: '旧金山',\n",
       "  10: '深圳',\n",
       "  11: '杭州',\n",
       "  12: '北京',\n",
       "  13: '北京',\n",
       "  14: '深圳',\n",
       "  15: '新加坡',\n",
       "  16: '洛杉矶',\n",
       "  17: '帕洛阿尔托',\n",
       "  18: '旧金山',\n",
       "  19: '北京',\n",
       "  20: '北京',\n",
       "  21: '圣地亚哥',\n",
       "  22: '雅加达',\n",
       "  23: '诺伊达',\n",
       "  24: '天津',\n",
       "  25: '北京',\n",
       "  26: '首尔',\n",
       "  27: '上海',\n",
       "  28: '旧金山',\n",
       "  29: '旧金山',\n",
       "  30: '门洛帕克',\n",
       "  31: '旧金山',\n",
       "  32: '门洛帕克',\n",
       "  33: 'Harrisburg',\n",
       "  34: '北京',\n",
       "  35: '上海',\n",
       "  36: '巴塞尔',\n",
       "  37: '南京',\n",
       "  38: 'Emerville',\n",
       "  39: '雅加达',\n",
       "  40: '匹兹堡',\n",
       "  41: '纽约',\n",
       "  42: '班加罗尔',\n",
       "  43: '贵阳',\n",
       "  44: 'Plantation',\n",
       "  45: '班加罗尔',\n",
       "  46: '北京',\n",
       "  47: '天津',\n",
       "  48: '杭州',\n",
       "  49: '城南市',\n",
       "  50: '新加坡',\n",
       "  51: '帕洛阿尔托',\n",
       "  52: '古尔冈',\n",
       "  53: '旧金山',\n",
       "  54: '普利茅斯',\n",
       "  55: '曼彻斯特',\n",
       "  56: '柏林',\n",
       "  57: '纽约',\n",
       "  58: '旧金山',\n",
       "  59: '加迪纳',\n",
       "  60: '帕洛阿尔托',\n",
       "  61: '坎布里奇',\n",
       "  62: '斯德哥尔摩',\n",
       "  63: '北京',\n",
       "  64: '上海',\n",
       "  65: '旧金山',\n",
       "  66: '圣保罗',\n",
       "  67: '旧金山',\n",
       "  68: '达拉斯',\n",
       "  69: '深圳',\n",
       "  70: '旧金山',\n",
       "  71: '圣马特奥',\n",
       "  72: '旧金山',\n",
       "  73: '伦敦',\n",
       "  74: '雅加达',\n",
       "  75: '帕洛阿尔托',\n",
       "  76: '深圳',\n",
       "  77: '上海',\n",
       "  78: '上海',\n",
       "  79: '广州',\n",
       "  80: '北京',\n",
       "  81: '古尔冈',\n",
       "  82: '伦敦',\n",
       "  83: '旧金山',\n",
       "  84: '圣何塞',\n",
       "  85: '北京',\n",
       "  86: '旧金山',\n",
       "  87: '杭州',\n",
       "  88: '悉尼',\n",
       "  89: '上海',\n",
       "  90: '波士顿',\n",
       "  91: '广州',\n",
       "  92: '帕洛阿尔托',\n",
       "  93: '深圳',\n",
       "  94: '旧金山',\n",
       "  95: '武汉',\n",
       "  96: '北京',\n",
       "  97: '旧金山',\n",
       "  98: '圣塔莫尼卡',\n",
       "  99: '上海',\n",
       "  100: '上海',\n",
       "  101: '上海',\n",
       "  102: '北京',\n",
       "  103: '南京',\n",
       "  104: '门洛帕克',\n",
       "  105: '深圳',\n",
       "  106: '北京',\n",
       "  107: '伦敦',\n",
       "  108: '柏林',\n",
       "  109: '旧金山',\n",
       "  110: '伦敦',\n",
       "  111: '阿林顿',\n",
       "  112: '纽约',\n",
       "  113: '诺伊达',\n",
       "  114: '旧金山',\n",
       "  115: '卡平特里亚',\n",
       "  116: '北京',\n",
       "  117: '旧金山',\n",
       "  118: '圣马特奥',\n",
       "  119: '旧金山',\n",
       "  120: '北京',\n",
       "  121: '纳什维尔',\n",
       "  122: '北京',\n",
       "  123: '班加罗尔',\n",
       "  124: '芝加哥',\n",
       "  125: '波士顿',\n",
       "  126: '旧金山',\n",
       "  127: '北京',\n",
       "  128: '北京',\n",
       "  129: '首尔',\n",
       "  130: '上海',\n",
       "  131: '上海',\n",
       "  132: '北京',\n",
       "  133: '上海',\n",
       "  134: '北京',\n",
       "  135: 'Foster City',\n",
       "  136: '北京',\n",
       "  137: '山景城',\n",
       "  138: '华盛顿',\n",
       "  139: '上海',\n",
       "  140: '帕洛阿尔托',\n",
       "  141: '北京',\n",
       "  142: '旧金山',\n",
       "  143: '帕洛阿尔托',\n",
       "  144: '芝加哥',\n",
       "  145: '伦敦',\n",
       "  146: '艾哈迈达巴德',\n",
       "  147: '-',\n",
       "  148: '圣塔莫尼卡',\n",
       "  149: '巴黎',\n",
       "  150: '香港',\n",
       "  151: '纽约',\n",
       "  152: '南京',\n",
       "  153: '北京',\n",
       "  154: '上海',\n",
       "  155: '雷德伍德城',\n",
       "  156: '帕洛阿尔托',\n",
       "  157: '伦敦',\n",
       "  158: '北京',\n",
       "  159: '旧金山',\n",
       "  160: '巴登符腾堡州',\n",
       "  161: '坎布里奇',\n",
       "  162: '纽约',\n",
       "  163: '古尔冈',\n",
       "  164: '伦敦',\n",
       "  165: 'Burlington Massachussets',\n",
       "  166: '沃尔瑟姆',\n",
       "  167: '楚格',\n",
       "  168: '旧金山',\n",
       "  169: '慕尼黑',\n",
       "  170: '圣布鲁诺',\n",
       "  171: '纽约',\n",
       "  172: '布里斯托尔',\n",
       "  173: '旧金山',\n",
       "  174: '旧金山',\n",
       "  175: '雷德伍德城',\n",
       "  176: '雷德伍德城',\n",
       "  177: '伦敦',\n",
       "  178: '特拉维夫',\n",
       "  179: '普若佛市',\n",
       "  180: '纽约',\n",
       "  181: '成都',\n",
       "  182: '都柏林',\n",
       "  183: '北京',\n",
       "  184: '雷霍沃特',\n",
       "  185: '纽约',\n",
       "  186: '圣马特奥',\n",
       "  187: '北京',\n",
       "  188: '奥克兰',\n",
       "  189: '广州',\n",
       "  190: '特拉维夫',\n",
       "  191: '奥斯汀',\n",
       "  192: '班加罗尔',\n",
       "  193: '卡尔弗城',\n",
       "  194: '旧金山',\n",
       "  195: '斯科茨代尔',\n",
       "  196: '斯德哥尔摩',\n",
       "  197: '牛津',\n",
       "  198: '旧金山',\n",
       "  199: '杭州',\n",
       "  200: '菲蒙市',\n",
       "  201: '旧金山',\n",
       "  202: '东京',\n",
       "  203: '森尼维耳市',\n",
       "  204: '山景城',\n",
       "  205: '深圳',\n",
       "  206: '古尔冈',\n",
       "  207: '伦敦',\n",
       "  208: '旧金山',\n",
       "  209: '格兰岱尔市',\n",
       "  210: '亚特兰大',\n",
       "  211: '纽约',\n",
       "  212: '纽约',\n",
       "  213: '伯班克',\n",
       "  214: '南京',\n",
       "  215: '杭州',\n",
       "  216: '芝加哥',\n",
       "  217: '-',\n",
       "  218: '上海',\n",
       "  219: '旧金山',\n",
       "  220: '北京',\n",
       "  221: '纽约',\n",
       "  222: '山景城',\n",
       "  223: '上海',\n",
       "  224: '杭州',\n",
       "  225: '北京',\n",
       "  226: '杭州',\n",
       "  227: '绍兴',\n",
       "  228: '北京',\n",
       "  229: '上海',\n",
       "  230: '北京',\n",
       "  231: '北京',\n",
       "  232: '北京',\n",
       "  233: '北京',\n",
       "  234: '北京',\n",
       "  235: '上海',\n",
       "  236: '南京',\n",
       "  237: '香港',\n",
       "  238: '上海',\n",
       "  239: '北京',\n",
       "  240: '上海',\n",
       "  241: '北京',\n",
       "  242: '杭州',\n",
       "  243: '天津',\n",
       "  244: '杭州',\n",
       "  245: '深圳',\n",
       "  246: '青岛',\n",
       "  247: '深圳',\n",
       "  248: '北京',\n",
       "  249: '南京',\n",
       "  250: '张家口',\n",
       "  251: '杭州',\n",
       "  252: '深圳',\n",
       "  253: '上海',\n",
       "  254: '北京',\n",
       "  255: '杭州',\n",
       "  256: '北京',\n",
       "  257: '上海',\n",
       "  258: '上海',\n",
       "  259: '北京',\n",
       "  260: '成都',\n",
       "  261: '重庆',\n",
       "  262: '上海',\n",
       "  263: '北京',\n",
       "  264: '普莱森顿',\n",
       "  265: '上海',\n",
       "  266: '成都',\n",
       "  267: '北京',\n",
       "  268: '北京',\n",
       "  269: '汉堡',\n",
       "  270: '沃尔瑟姆',\n",
       "  271: '格兰岱尔市',\n",
       "  272: '旧金山',\n",
       "  273: '香港',\n",
       "  274: '深圳',\n",
       "  275: '上海',\n",
       "  276: '旧金山',\n",
       "  277: '尔湾',\n",
       "  278: '上海',\n",
       "  279: '上海',\n",
       "  280: '旧金山',\n",
       "  281: '布宜诺斯艾利斯',\n",
       "  282: '旧金山',\n",
       "  283: '夏洛特市',\n",
       "  284: '纽约',\n",
       "  285: '上海',\n",
       "  286: '杭州',\n",
       "  287: '班加罗尔',\n",
       "  288: '帕洛阿尔托',\n",
       "  289: '旧金山',\n",
       "  290: '塔林',\n",
       "  291: '上海',\n",
       "  292: '南京',\n",
       "  293: '雷德伍德城',\n",
       "  294: '雅加达',\n",
       "  295: 'Guilford',\n",
       "  296: '雷德伍德城',\n",
       "  297: '马德里',\n",
       "  298: '旧金山',\n",
       "  299: '南京',\n",
       "  300: '纽约',\n",
       "  301: '罗利',\n",
       "  302: '坎贝尔',\n",
       "  303: '杭州',\n",
       "  304: '南京',\n",
       "  305: '北京',\n",
       "  306: '旧金山',\n",
       "  307: '旧金山',\n",
       "  308: '圣何塞',\n",
       "  309: '纽约',\n",
       "  310: '耐斯兹敖那',\n",
       "  311: '西雅图',\n",
       "  312: '山景城',\n",
       "  313: '上海',\n",
       "  314: '北京',\n",
       "  315: '波士顿',\n",
       "  316: '波士顿',\n",
       "  317: '巴黎',\n",
       "  318: '上海',\n",
       "  319: '旧金山',\n",
       "  320: '巴黎',\n",
       "  321: '上海',\n",
       "  322: '波士顿',\n",
       "  323: '孟买',\n",
       "  324: '森尼维耳市',\n",
       "  325: '杭州',\n",
       "  326: '杭州',\n",
       "  327: '北京',\n",
       "  328: '上海',\n",
       "  329: '雷德伍德城',\n",
       "  330: '波士顿',\n",
       "  331: '圣塔莫尼卡',\n",
       "  332: '深圳',\n",
       "  333: '上海',\n",
       "  334: '深圳',\n",
       "  335: '萨默维尔市',\n",
       "  336: '北京',\n",
       "  337: '北京',\n",
       "  338: '北京',\n",
       "  339: '柏林',\n",
       "  340: '波士顿',\n",
       "  341: '旧金山',\n",
       "  342: '卢森堡',\n",
       "  343: '纽约',\n",
       "  344: '圣保罗',\n",
       "  345: '北京',\n",
       "  346: '盐湖城',\n",
       "  347: '新德里',\n",
       "  348: '旧金山',\n",
       "  349: '赫尔辛基',\n",
       "  350: '南京',\n",
       "  351: '桐乡',\n",
       "  352: '无锡',\n",
       "  353: '北京',\n",
       "  354: '上海',\n",
       "  355: '圣地亚哥',\n",
       "  356: '广州',\n",
       "  357: '-',\n",
       "  358: '圣保罗',\n",
       "  359: '南京',\n",
       "  360: '森尼维耳市',\n",
       "  361: '班加罗尔',\n",
       "  362: '旧金山',\n",
       "  363: '重庆',\n",
       "  364: '特拉维夫',\n",
       "  365: '上海',\n",
       "  366: '雷德伍德城',\n",
       "  367: '森尼维耳市',\n",
       "  368: '北京',\n",
       "  369: '杭州',\n",
       "  370: '广州',\n",
       "  371: '成都',\n",
       "  372: '北京',\n",
       "  373: '亚特兰大',\n",
       "  374: '旧金山',\n",
       "  375: '奥斯汀',\n",
       "  376: '克利尔沃特',\n",
       "  377: '北京',\n",
       "  378: '北京',\n",
       "  379: '香港',\n",
       "  380: '深圳',\n",
       "  381: '金华',\n",
       "  382: '纽约',\n",
       "  383: '杭州',\n",
       "  384: '耶路撒冷',\n",
       "  385: '北京',\n",
       "  386: '深圳',\n",
       "  387: '上海',\n",
       "  388: '东京',\n",
       "  389: '圣保罗',\n",
       "  390: '北京',\n",
       "  391: '旧金山',\n",
       "  392: '北京',\n",
       "  393: '北京',\n",
       "  394: '圣卡洛斯',\n",
       "  395: '纽约',\n",
       "  396: '巴黎',\n",
       "  397: '旧金山',\n",
       "  398: '北京',\n",
       "  399: 'Stafford',\n",
       "  400: '洛桑市',\n",
       "  401: '北京',\n",
       "  402: '上海',\n",
       "  403: '北京',\n",
       "  404: '纽约',\n",
       "  405: '圣克拉拉',\n",
       "  406: '菲尼克斯',\n",
       "  407: '广州',\n",
       "  408: '北京',\n",
       "  409: '贝尔维尤',\n",
       "  410: '班加罗尔',\n",
       "  411: '柏林',\n",
       "  412: '旧金山',\n",
       "  413: '亚特兰大',\n",
       "  414: '深圳',\n",
       "  415: '耶路撒冷',\n",
       "  416: '西雅图',\n",
       "  417: '波士顿',\n",
       "  418: '布里斯托尔',\n",
       "  419: '迈阿密',\n",
       "  420: '纽约',\n",
       "  421: '上海',\n",
       "  422: '古尔冈',\n",
       "  423: '台北',\n",
       "  424: '雷德伍德城',\n",
       "  425: '班加罗尔',\n",
       "  426: '芝加哥',\n",
       "  427: '波哥大',\n",
       "  428: '北京',\n",
       "  429: '北京',\n",
       "  430: '纽约',\n",
       "  431: '马卡迪',\n",
       "  432: '古尔冈',\n",
       "  433: '杭廷顿海滩',\n",
       "  434: '哥伦布',\n",
       "  435: '亚特兰大',\n",
       "  436: '圣地亚哥',\n",
       "  437: '古尔冈',\n",
       "  438: '北京',\n",
       "  439: '北京',\n",
       "  440: '阿拉米达',\n",
       "  441: '北京',\n",
       "  442: '北京',\n",
       "  443: '旧金山',\n",
       "  444: '圣克拉拉',\n",
       "  445: '底特律',\n",
       "  446: '雷德伍德城',\n",
       "  447: '卡尔弗城',\n",
       "  448: '帕洛阿尔托',\n",
       "  449: '纽约',\n",
       "  450: '旧金山',\n",
       "  451: '北京',\n",
       "  452: '山景城',\n",
       "  453: '埃尔塞贡多',\n",
       "  454: '北京',\n",
       "  455: '圣塔莫尼卡',\n",
       "  456: '森尼维耳市',\n",
       "  457: '旧金山',\n",
       "  458: '首尔',\n",
       "  459: '首尔',\n",
       "  460: '旧金山',\n",
       "  461: '夏洛特市',\n",
       "  462: '旧金山',\n",
       "  463: '圣地亚哥',\n",
       "  464: '上海',\n",
       "  465: '班加罗尔',\n",
       "  466: '山景城',\n",
       "  467: '北京',\n",
       "  468: '上海',\n",
       "  469: '苗必达',\n",
       "  470: '旧金山',\n",
       "  471: '华盛顿',\n",
       "  472: '纽约',\n",
       "  473: '杭州',\n",
       "  474: '旧金山',\n",
       "  475: '香港',\n",
       "  476: '上海',\n",
       "  477: '北京',\n",
       "  478: '广州',\n",
       "  479: '首尔',\n",
       "  480: '广州',\n",
       "  481: '深圳',\n",
       "  482: '北京',\n",
       "  483: '北京',\n",
       "  484: '上海',\n",
       "  485: '上海',\n",
       "  486: '北京',\n",
       "  487: '北京',\n",
       "  488: '北京',\n",
       "  489: '纽约',\n",
       "  490: '上海',\n",
       "  491: '北京',\n",
       "  492: '半月湾',\n",
       "  493: '洛杉矶'},\n",
       " '行业': {0: '金融科技',\n",
       "  1: '媒体和娱乐',\n",
       "  2: '共享经济',\n",
       "  3: '云计算',\n",
       "  4: '消费品',\n",
       "  5: '共享经济',\n",
       "  6: '金融科技',\n",
       "  7: '航天',\n",
       "  8: '共享经济',\n",
       "  9: '金融科技',\n",
       "  10: '金融科技',\n",
       "  11: '物流',\n",
       "  12: '金融科技',\n",
       "  13: '媒体和娱乐',\n",
       "  14: '机器人',\n",
       "  15: '共享经济',\n",
       "  16: '媒体和娱乐',\n",
       "  17: '大数据',\n",
       "  18: '物流',\n",
       "  19: '区块链',\n",
       "  20: '物流',\n",
       "  21: '生命科学',\n",
       "  22: '共享经济',\n",
       "  23: '金融科技',\n",
       "  24: '房地产科技',\n",
       "  25: '电子商务',\n",
       "  26: '电子商务',\n",
       "  27: '健康科技',\n",
       "  28: '电子商务',\n",
       "  29: '区块链',\n",
       "  30: '生命科学',\n",
       "  31: '物流',\n",
       "  32: '金融科技',\n",
       "  33: '人工智能',\n",
       "  34: '电子商务',\n",
       "  35: '金融科技',\n",
       "  36: '生命科学',\n",
       "  37: '金融科技',\n",
       "  38: '网络安全',\n",
       "  39: '电子商务',\n",
       "  40: '共享经济',\n",
       "  41: '人工智能',\n",
       "  42: '教育科技',\n",
       "  43: '物流',\n",
       "  44: '虚拟与增强现实',\n",
       "  45: '共享经济',\n",
       "  46: '人工智能',\n",
       "  47: '共享经济',\n",
       "  48: '健康科技',\n",
       "  49: '游戏',\n",
       "  50: '电子商务',\n",
       "  51: '游戏',\n",
       "  52: '共享经济',\n",
       "  53: '区块链',\n",
       "  54: '新能源汽车',\n",
       "  55: '电子商务',\n",
       "  56: '电子商务',\n",
       "  57: '电子商务',\n",
       "  58: '金融科技',\n",
       "  59: '新能源汽车',\n",
       "  60: '电子商务',\n",
       "  61: '生命科学',\n",
       "  62: '金融科技',\n",
       "  63: '人工智能',\n",
       "  64: '物流',\n",
       "  65: '虚拟与增强现实',\n",
       "  66: '金融科技',\n",
       "  67: '电子商务',\n",
       "  68: '生命科学',\n",
       "  69: '消费品',\n",
       "  70: '云计算',\n",
       "  71: '大数据',\n",
       "  72: '金融科技',\n",
       "  73: '金融科技',\n",
       "  74: '电子商务',\n",
       "  75: '电子商务',\n",
       "  76: '机器人',\n",
       "  77: '健康科技',\n",
       "  78: '新能源汽车',\n",
       "  79: '新能源汽车',\n",
       "  80: '房地产科技',\n",
       "  81: '物流',\n",
       "  82: '金融科技',\n",
       "  83: '金融科技',\n",
       "  84: '人工智能',\n",
       "  85: '媒体和娱乐',\n",
       "  86: '金融科技',\n",
       "  87: '区块链',\n",
       "  88: '云计算',\n",
       "  89: '金融科技',\n",
       "  90: '区块链',\n",
       "  91: '人工智能',\n",
       "  92: '云计算',\n",
       "  93: '媒体和娱乐',\n",
       "  94: '大数据',\n",
       "  95: '媒体和娱乐',\n",
       "  96: '金融科技',\n",
       "  97: '物流',\n",
       "  98: '健康科技',\n",
       "  99: '共享经济',\n",
       "  100: '生命科学',\n",
       "  101: '媒体和娱乐',\n",
       "  102: '人工智能',\n",
       "  103: '电子商务',\n",
       "  104: '房地产科技',\n",
       "  105: '物流',\n",
       "  106: '电子商务',\n",
       "  107: '金融科技',\n",
       "  108: '金融科技',\n",
       "  109: '机器人',\n",
       "  110: '金融科技',\n",
       "  111: '航天',\n",
       "  112: '健康科技',\n",
       "  113: '电子商务',\n",
       "  114: '金融科技',\n",
       "  115: '房地产科技',\n",
       "  116: '网络安全',\n",
       "  117: '媒体和娱乐',\n",
       "  118: '游戏',\n",
       "  119: '云计算',\n",
       "  120: '新能源汽车',\n",
       "  121: '健康科技',\n",
       "  122: '电子商务',\n",
       "  123: '物流',\n",
       "  124: '生命科学',\n",
       "  125: '金融科技',\n",
       "  126: '游戏',\n",
       "  127: '共享经济',\n",
       "  128: '教育科技',\n",
       "  129: '物流',\n",
       "  130: '软件与服务',\n",
       "  131: '电子商务',\n",
       "  132: '媒体和娱乐',\n",
       "  133: '新能源汽车',\n",
       "  134: '教育科技',\n",
       "  135: '人工智能',\n",
       "  136: '教育科技',\n",
       "  137: '生命科学',\n",
       "  138: '人工智能',\n",
       "  139: '软件与服务',\n",
       "  140: '游戏',\n",
       "  141: '软件与服务',\n",
       "  142: '云计算',\n",
       "  143: '人工智能',\n",
       "  144: '金融科技',\n",
       "  145: '人工智能',\n",
       "  146: '金融科技',\n",
       "  147: '区块链',\n",
       "  148: '共享经济',\n",
       "  149: '共享经济',\n",
       "  150: '区块链',\n",
       "  151: '媒体和娱乐',\n",
       "  152: '新能源汽车',\n",
       "  153: '人工智能',\n",
       "  154: '媒体和娱乐',\n",
       "  155: '3D印刷',\n",
       "  156: '金融科技',\n",
       "  157: '金融科技',\n",
       "  158: '新能源汽车',\n",
       "  159: '金融科技',\n",
       "  160: '生命科学',\n",
       "  161: '人工智能',\n",
       "  162: '人工智能',\n",
       "  163: '物流',\n",
       "  164: '物流',\n",
       "  165: '3D印刷',\n",
       "  166: '健康科技',\n",
       "  167: '区块链',\n",
       "  168: '即时通讯',\n",
       "  169: '电子商务',\n",
       "  170: '云计算',\n",
       "  171: '物流',\n",
       "  172: '人工智能',\n",
       "  173: '金融科技',\n",
       "  174: '云计算',\n",
       "  175: '健康科技',\n",
       "  176: '新零售',\n",
       "  177: '游戏',\n",
       "  178: '云计算',\n",
       "  179: '人工智能',\n",
       "  180: '云计算',\n",
       "  181: '物流',\n",
       "  182: '云计算',\n",
       "  183: '云计算',\n",
       "  184: '软件与服务',\n",
       "  185: '金融科技',\n",
       "  186: '共享经济',\n",
       "  187: '电子商务',\n",
       "  188: '金融科技',\n",
       "  189: '新零售',\n",
       "  190: '云计算',\n",
       "  191: '金融科技',\n",
       "  192: '大数据',\n",
       "  193: '生命科学',\n",
       "  194: '即时通讯',\n",
       "  195: '消费品',\n",
       "  196: '新能源',\n",
       "  197: '生命科学',\n",
       "  198: '消费品',\n",
       "  199: '金融科技',\n",
       "  200: '人工智能',\n",
       "  201: '物流',\n",
       "  202: '人工智能',\n",
       "  203: '软件与服务',\n",
       "  204: '媒体和娱乐',\n",
       "  205: '消费品',\n",
       "  206: '新能源',\n",
       "  207: '金融科技',\n",
       "  208: '云计算',\n",
       "  209: '云计算',\n",
       "  210: '健康科技',\n",
       "  211: '云计算',\n",
       "  212: '云计算',\n",
       "  213: '媒体和娱乐',\n",
       "  214: '媒体和娱乐',\n",
       "  215: '电子商务',\n",
       "  216: '人工智能',\n",
       "  217: '消费品',\n",
       "  218: '人工智能',\n",
       "  219: '云计算',\n",
       "  220: '媒体和娱乐',\n",
       "  221: '健康科技',\n",
       "  222: '物流',\n",
       "  223: '新能源汽车',\n",
       "  224: '共享经济',\n",
       "  225: '房地产科技',\n",
       "  226: '区块链',\n",
       "  227: '新能源汽车',\n",
       "  228: '软件与服务',\n",
       "  229: '教育科技',\n",
       "  230: '游戏',\n",
       "  231: '电子商务',\n",
       "  232: '大数据',\n",
       "  233: '软件与服务',\n",
       "  234: '健康科技',\n",
       "  235: '媒体和娱乐',\n",
       "  236: '电子商务',\n",
       "  237: '电子商务',\n",
       "  238: '电子商务',\n",
       "  239: '电子商务',\n",
       "  240: '房地产科技',\n",
       "  241: '人工智能',\n",
       "  242: '媒体和娱乐',\n",
       "  243: '机器人',\n",
       "  244: '大数据',\n",
       "  245: '健康科技',\n",
       "  246: '物流',\n",
       "  247: '电子商务',\n",
       "  248: '物流',\n",
       "  249: '新能源汽车',\n",
       "  250: '大数据',\n",
       "  251: '云计算',\n",
       "  252: '软件与服务',\n",
       "  253: '电子商务',\n",
       "  254: '共享经济',\n",
       "  255: '人工智能',\n",
       "  256: '电子商务',\n",
       "  257: '消费品',\n",
       "  258: '生命科学',\n",
       "  259: '房地产科技',\n",
       "  260: '媒体和娱乐',\n",
       "  261: '软件与服务',\n",
       "  262: '电子商务',\n",
       "  263: '金融科技',\n",
       "  264: '生命科学',\n",
       "  265: '教育科技',\n",
       "  266: '新零售',\n",
       "  267: '人工智能',\n",
       "  268: '金融科技',\n",
       "  269: '电子商务',\n",
       "  270: '云计算',\n",
       "  271: '教育科技',\n",
       "  272: '云计算',\n",
       "  273: '金融科技',\n",
       "  274: '金融科技',\n",
       "  275: '媒体和娱乐',\n",
       "  276: '新零售',\n",
       "  277: '健康科技',\n",
       "  278: '物流',\n",
       "  279: '健康科技',\n",
       "  280: '电子商务',\n",
       "  281: '云计算',\n",
       "  282: '云计算',\n",
       "  283: '金融科技',\n",
       "  284: '新零售',\n",
       "  285: '人工智能',\n",
       "  286: '电子商务',\n",
       "  287: '新零售',\n",
       "  288: '金融科技',\n",
       "  289: '区块链',\n",
       "  290: '共享经济',\n",
       "  291: '电子商务',\n",
       "  292: '新能源汽车',\n",
       "  293: '软件与服务',\n",
       "  294: '电子商务',\n",
       "  295: '健康科技',\n",
       "  296: '人工智能',\n",
       "  297: '共享经济',\n",
       "  298: '健康科技',\n",
       "  299: '新零售',\n",
       "  300: '新零售',\n",
       "  301: '大数据',\n",
       "  302: '新能源',\n",
       "  303: '电子商务',\n",
       "  304: '电子商务',\n",
       "  305: '健康科技',\n",
       "  306: '网络安全',\n",
       "  307: '人工智能',\n",
       "  308: '云计算',\n",
       "  309: '大数据',\n",
       "  310: '云计算',\n",
       "  311: '物流',\n",
       "  312: '教育科技',\n",
       "  313: '教育科技',\n",
       "  314: '软件与服务',\n",
       "  315: '人工智能',\n",
       "  316: '软件与服务',\n",
       "  317: '媒体和娱乐',\n",
       "  318: '金融科技',\n",
       "  319: '云计算',\n",
       "  320: '健康科技',\n",
       "  321: '大数据',\n",
       "  322: '游戏',\n",
       "  323: '游戏',\n",
       "  324: '云计算',\n",
       "  325: '云计算',\n",
       "  326: '健康科技',\n",
       "  327: '金融科技',\n",
       "  328: '新能源',\n",
       "  329: '云计算',\n",
       "  330: '电子商务',\n",
       "  331: '电子商务',\n",
       "  332: '房地产科技',\n",
       "  333: '电子商务',\n",
       "  334: '物流',\n",
       "  335: '3D印刷',\n",
       "  336: '软件与服务',\n",
       "  337: '人工智能',\n",
       "  338: '大数据',\n",
       "  339: '电子商务',\n",
       "  340: '生命科学',\n",
       "  341: '云计算',\n",
       "  342: '电子商务',\n",
       "  343: '消费品',\n",
       "  344: '健康科技',\n",
       "  345: '健康科技',\n",
       "  346: '大数据',\n",
       "  347: '即时通讯',\n",
       "  348: '电子商务',\n",
       "  349: '消费品',\n",
       "  350: '软件与服务',\n",
       "  351: '新能源汽车',\n",
       "  352: '大数据',\n",
       "  353: '教育科技',\n",
       "  354: '教育科技',\n",
       "  355: '生命科学',\n",
       "  356: '健康科技',\n",
       "  357: '云计算',\n",
       "  358: '物流',\n",
       "  359: '软件与服务',\n",
       "  360: '网络安全',\n",
       "  361: '软件与服务',\n",
       "  362: '即时通讯',\n",
       "  363: '电子商务',\n",
       "  364: '生命科学',\n",
       "  365: '教育科技',\n",
       "  366: '云计算',\n",
       "  367: '云计算',\n",
       "  368: '电子商务',\n",
       "  369: '电子商务',\n",
       "  370: '电子商务',\n",
       "  371: '物流',\n",
       "  372: '大数据',\n",
       "  373: '金融科技',\n",
       "  374: '物流',\n",
       "  375: '新零售',\n",
       "  376: '网络安全',\n",
       "  377: '教育科技',\n",
       "  378: '共享经济',\n",
       "  379: '物流',\n",
       "  380: '健康科技',\n",
       "  381: '新能源汽车',\n",
       "  382: '电子商务',\n",
       "  383: '金融科技',\n",
       "  384: '云计算',\n",
       "  385: '大数据',\n",
       "  386: '金融科技',\n",
       "  387: '媒体和娱乐',\n",
       "  388: '区块链',\n",
       "  389: '物流',\n",
       "  390: '物流',\n",
       "  391: '网络安全',\n",
       "  392: '媒体和娱乐',\n",
       "  393: '软件与服务',\n",
       "  394: '大数据',\n",
       "  395: '电子商务',\n",
       "  396: '人工智能',\n",
       "  397: '云计算',\n",
       "  398: '健康科技',\n",
       "  399: '新能源',\n",
       "  400: '虚拟与增强现实',\n",
       "  401: '人工智能',\n",
       "  402: '人工智能',\n",
       "  403: '人工智能',\n",
       "  404: '金融科技',\n",
       "  405: '云计算',\n",
       "  406: '新能源汽车',\n",
       "  407: '新零售',\n",
       "  408: '生命科学',\n",
       "  409: '电子商务',\n",
       "  410: '共享经济',\n",
       "  411: '电子商务',\n",
       "  412: '健康科技',\n",
       "  413: '网络安全',\n",
       "  414: '人工智能',\n",
       "  415: '人工智能',\n",
       "  416: '云计算',\n",
       "  417: '云计算',\n",
       "  418: '新能源',\n",
       "  419: '房地产科技',\n",
       "  420: '消费品',\n",
       "  421: '电子商务',\n",
       "  422: '金融科技',\n",
       "  423: '新能源',\n",
       "  424: '健康科技',\n",
       "  425: '电子商务',\n",
       "  426: '金融科技',\n",
       "  427: '物流',\n",
       "  428: '电子商务',\n",
       "  429: '金融科技',\n",
       "  430: '电子商务',\n",
       "  431: '房地产科技',\n",
       "  432: '物流',\n",
       "  433: '航天',\n",
       "  434: '金融科技',\n",
       "  435: '新能源',\n",
       "  436: '人工智能',\n",
       "  437: '电子商务',\n",
       "  438: '共享经济',\n",
       "  439: '金融科技',\n",
       "  440: '新能源',\n",
       "  441: '生命科学',\n",
       "  442: '消费品',\n",
       "  443: '房地产科技',\n",
       "  444: '人工智能',\n",
       "  445: '电子商务',\n",
       "  446: '云计算',\n",
       "  447: '新零售',\n",
       "  448: '即时通讯',\n",
       "  449: '软件与服务',\n",
       "  450: '人工智能',\n",
       "  451: '大数据',\n",
       "  452: '即时通讯',\n",
       "  453: '电子商务',\n",
       "  454: '健康科技',\n",
       "  455: '消费品',\n",
       "  456: '人工智能',\n",
       "  457: '电子商务',\n",
       "  458: '电子商务',\n",
       "  459: '金融科技',\n",
       "  460: '云计算',\n",
       "  461: '大数据',\n",
       "  462: '共享经济',\n",
       "  463: '人工智能',\n",
       "  464: '云计算',\n",
       "  465: '电子商务',\n",
       "  466: '教育科技',\n",
       "  467: '云计算',\n",
       "  468: '房地产科技',\n",
       "  469: '新能源',\n",
       "  470: '云计算',\n",
       "  471: '媒体和娱乐',\n",
       "  472: '房地产科技',\n",
       "  473: '金融科技',\n",
       "  474: '云计算',\n",
       "  475: '金融科技',\n",
       "  476: '软件与服务',\n",
       "  477: '电子商务',\n",
       "  478: '软件与服务',\n",
       "  479: '电子商务',\n",
       "  480: '电子商务',\n",
       "  481: '物流',\n",
       "  482: '媒体和娱乐',\n",
       "  483: '电子商务',\n",
       "  484: '物流',\n",
       "  485: '电子商务',\n",
       "  486: '金融科技',\n",
       "  487: '软件与服务',\n",
       "  488: '物流',\n",
       "  489: '人工智能',\n",
       "  490: '教育科技',\n",
       "  491: '电子商务',\n",
       "  492: '物流',\n",
       "  493: '电子商务'},\n",
       " '掌门人/创始人': {0: '井贤栋',\n",
       "  1: '张一鸣',\n",
       "  2: '程维',\n",
       "  3: 'Jim Schaper',\n",
       "  4: 'Adam Bowen, James Monsees, Kevin Burns, Tim Danaher',\n",
       "  5: 'Brian Chesky, Joe Gebbia, Nathan Blecharczyk',\n",
       "  6: '计葵生',\n",
       "  7: 'Elon Musk',\n",
       "  8: 'Adam Neumann, Miguel McKevley',\n",
       "  9: 'John Collison, Patrick Collison',\n",
       "  10: '顾敏',\n",
       "  11: '童文红',\n",
       "  12: '陈生强',\n",
       "  13: '宿华',\n",
       "  14: '汪滔',\n",
       "  15: 'Anthony Tan,\\xa0Tan Hooi Ling',\n",
       "  16: 'Elizabeth Comstock,\\xa0Jason Kilar',\n",
       "  17: 'Alexander Karp,\\xa0Garry Tan,\\xa0Joe Lonsdale,\\xa0Nathan Gettings,\\xa0Peter Thiel,\\xa0Stephen Cohen',\n",
       "  18: 'Andy Fang,\\xa0Evan Moore,\\xa0Stanley Tang,\\xa0Tony Xu',\n",
       "  19: '詹克团，吴忌寒',\n",
       "  20: '王振辉',\n",
       "  21: 'Osman Kibar',\n",
       "  22: 'Kevin Aluwi,\\xa0Michaelangelo Moran,\\xa0Nadiem Makarim',\n",
       "  23: 'Vijay Shekhar Sharma',\n",
       "  24: '左晖',\n",
       "  25: '杨浩涌',\n",
       "  26: 'Bom Kim',\n",
       "  27: '高菁',\n",
       "  28: 'Danny Zhang,\\xa0Peter Szulczewski',\n",
       "  29: 'Brian Armstrong,\\xa0Fred Ehrsam',\n",
       "  30: 'Jeffrey Huber',\n",
       "  31: 'Apoorva Mehta,\\xa0Brandon Leonardo,\\xa0Max Mullen',\n",
       "  32: 'Baiju Bhatt,\\xa0Vlad Tenev',\n",
       "  33: 'Bryan Salesky, Peter Rander',\n",
       "  34: '刘传军',\n",
       "  35: '叶望春',\n",
       "  36: 'Vivek Ramaswamy',\n",
       "  37: '张近东',\n",
       "  38: 'David Hindawi,\\xa0Orion HindawiOperating\\xa0Status',\n",
       "  39: 'Leontinus Alpha Edison,\\xa0William Tanuwijaya',\n",
       "  40: '-',\n",
       "  41: 'Daniel Dines,\\xa0Marius Tirca',\n",
       "  42: 'Byju Raveendran,\\xa0Divya Gokulnath',\n",
       "  43: '王刚',\n",
       "  44: 'Brian Schowengerdt,\\xa0Rony Abovitz',\n",
       "  45: 'Ankit Bhati,\\xa0Bhavish Aggarwal',\n",
       "  46: '徐立',\n",
       "  47: '陆正耀',\n",
       "  48: '廖杰远',\n",
       "  49: 'Chang Byung-gyu',\n",
       "  50: 'Aimone Ripa di Meana,\\xa0Alexander Samwer,\\xa0Arthur Brejon de Lavergnee,\\xa0Bede Moore,\\xa0Elizabeth Craft,\\xa0Eugene Chistyakov,\\xa0Fung Lestario,\\xa0Inanc Balci,\\xa0James Chang,\\xa0Maximilian Bittner,\\xa0Oliver Samwer,\\xa0Stefan Bruun,\\xa0Stein Jakob Oeie,\\xa0Sundeep Sahni',\n",
       "  51: 'Gabriel Leydon,\\xa0Halbert Nakagawa,\\xa0Michael Sherrill',\n",
       "  52: 'Ritesh Agarwal',\n",
       "  53: 'Arthur Britto,\\xa0Chris Larsen,\\xa0Ryan Fugger',\n",
       "  54: 'Robert J. Scaringe',\n",
       "  55: 'John Gallemore, Matthew Moulding',\n",
       "  56: 'Christian Bertermann, Hakan Koc',\n",
       "  57: 'Ori Allon,\\xa0Robert Reffkin,\\xa0Ugo Di Girolamo',\n",
       "  58: 'Kenneth Lin, Nichole Mustard, Ryan Graciano',\n",
       "  59: 'Tony Nie',\n",
       "  60: 'Adi Tatarko,\\xa0Alon Cohen',\n",
       "  61: 'David Perry, Geoffrey von Maltzahn, Ignacio Martinez, Noubar Afeyan',\n",
       "  62: 'Niklas Adalberth, Sebastian Siemiatkowski, Victor Jacobsson',\n",
       "  63: '印奇',\n",
       "  64: '蒯佳祺',\n",
       "  65: 'John Hanke,\\xa0Phil Keslin',\n",
       "  66: 'Adam Edward Wible,\\xa0Cristina Junqueira,\\xa0David Velez',\n",
       "  67: 'Eric Wu, Ian Wong, Justin Ross, Keith Rabois',\n",
       "  68: 'Michael S. Brown,\\xa0Steven McKnight',\n",
       "  69: '刘自鸿',\n",
       "  70: 'John Bicket, Sanjit Biswas',\n",
       "  71: 'Thierry Cruanes, Marcin Zukowski, Benoit Dageville',\n",
       "  72: 'Daniel Macklin,\\xa0Ian Brady,\\xa0James Finnigan,\\xa0Michael Cagney',\n",
       "  73: 'Kristo Kaarmann, Taavet Hinrikus',\n",
       "  74: 'Albert Albert,\\xa0Derianto Kusuma,\\xa0Ferry Unardi',\n",
       "  75: 'Ariel Cohen,\\xa0Ilan Twig',\n",
       "  76: '周剑',\n",
       "  77: '薛敏',\n",
       "  78: '沈晖',\n",
       "  79: '何小鹏',\n",
       "  80: '左晖',\n",
       "  81: 'Deepinder Goyal,\\xa0Pankaj Chaddah',\n",
       "  82: 'Jason Austin, Lex Greensill',\n",
       "  83: 'Jeffrey Kaditz,\\xa0Max Levchin,\\xa0Nathan Gettings',\n",
       "  84: 'Ankur Kothari,\\xa0Mihir Shukla,\\xa0Neeti Mehta',\n",
       "  85: '于冬',\n",
       "  86: 'Henrique Dubugras,\\xa0Pedro Franceschi',\n",
       "  87: '张楠赓',\n",
       "  88: 'Cameron Adams,\\xa0Cliff Obrecht,\\xa0Melanie Perkins',\n",
       "  89: '田林',\n",
       "  90: 'Jeremy Allaire,\\xa0Sean Neville',\n",
       "  91: '周曦',\n",
       "  92: 'Jay Kreps,\\xa0Jun Rao,\\xa0Neha Narkhede',\n",
       "  93: '刘荣',\n",
       "  94: 'Ali Ghodsi,\\xa0Andy Konwinski,\\xa0Ion Stoica,\\xa0Matei Zaharia,\\xa0Patrick Wendell,\\xa0Reynold Xin,\\xa0Scott Shenker',\n",
       "  95: '陈少杰',\n",
       "  96: '朱光',\n",
       "  97: 'Ryan Petersen',\n",
       "  98: 'Doug Hirsch,\\xa0Scott Marlette,\\xa0Trevor Bezdek',\n",
       "  99: '杨磊',\n",
       "  100: '刘世高',\n",
       "  101: '余建军',\n",
       "  102: '余凯',\n",
       "  103: '徐秀贤',\n",
       "  104: 'Fritz H. Wolff,\\xa0Jim Davidson,\\xa0Michael Marks',\n",
       "  105: '胡永',\n",
       "  106: '徐正',\n",
       "  107: 'Gary Dolman,\\xa0Jason Bates,\\xa0Jonas Huckestein,\\xa0Paul Rippon,\\xa0Tom Blomfield',\n",
       "  108: 'Maximilian Tayenthal,\\xa0Valentin Stalf',\n",
       "  109: 'Dave Ferguson, Jiajun Zhu',\n",
       "  110: 'Joel Perlman,\\xa0Rishi Khosla',\n",
       "  111: 'Greg Wyler',\n",
       "  112: 'Joshua Kushner,\\xa0Mario Schlosser',\n",
       "  113: 'Vijay Shekhar Sharma',\n",
       "  114: 'William Hockey,\\xa0Zachary Perret',\n",
       "  115: 'Craig Courtemanche',\n",
       "  116: '齐向东',\n",
       "  117: 'Alexis Ohanian,\\xa0Steve Huffman',\n",
       "  118: 'David Baszucki',\n",
       "  119: 'Arvind Jain, Arvind Nithrakashyap, Bipul Sinha, Soham Mazumdar',\n",
       "  120: '沈海寅',\n",
       "  121: 'Alex Fenkell,\\xa0Jordan Katzman',\n",
       "  122: '姚军红',\n",
       "  123: 'Nandan Reddy,\\xa0Rahul Jaimini,\\xa0Sriharsha Majety',\n",
       "  124: 'Eric Lefkofsky',\n",
       "  125: 'Aman Narang,\\xa0Jonathan Grimm,\\xa0Steve Fredette',\n",
       "  126: 'David Helgason,\\xa0Joachim Ante,\\xa0Nicholas Francis',\n",
       "  127: '毛大庆',\n",
       "  128: '米雯娟',\n",
       "  129: 'Bong Jin Kim',\n",
       "  130: '毛文超',\n",
       "  131: '金光磊',\n",
       "  132: '韩坤',\n",
       "  133: '卫俊',\n",
       "  134: '李勇',\n",
       "  135: 'Jesse Levinson,\\xa0Tim Kentley-Klay',\n",
       "  136: '侯建彬',\n",
       "  137: 'Anne Wojcicki,\\xa0Linda Avey,\\xa0Paul Cusenza',\n",
       "  138: 'Zia Chishti',\n",
       "  139: '陈雪峰',\n",
       "  140: 'Adam Foroughi,\\xa0Andrew Karam,\\xa0John Krystynak',\n",
       "  141: '李涛',\n",
       "  142: 'Dustin Moskovitz,\\xa0Justin Rosenstein',\n",
       "  143: 'Chris Urmson,\\xa0J. Andrew Bagnell,\\xa0Sterling Anderson',\n",
       "  144: 'Al Goldstein,\\xa0John Sun,\\xa0Paul Zhang',\n",
       "  145: 'Brent Gutekunst,\\xa0Ivan Griffin,\\xa0Ken Mulvany,\\xa0Michael Brennan',\n",
       "  146: 'Karthik Ganapathy, Ajay Kaushal, MN Srinivasu',\n",
       "  147: '赵长鹏、何一',\n",
       "  148: 'Travis VanderZanden',\n",
       "  149: 'Francis Nappez,\\xa0Frédéric Mazzella,\\xa0Nicolas Brusson',\n",
       "  150: 'Brendan Blumer',\n",
       "  151: 'John Johnson,\\xa0Jonah Peretti',\n",
       "  152: '毕福康',\n",
       "  153: '陈天石',\n",
       "  154: '田明',\n",
       "  155: 'Joseph M. DeSimone,\\xa0Philip DeSimone',\n",
       "  156: 'Henry Ward,\\xa0Manu Kumar',\n",
       "  157: 'Guillaume Pousaz',\n",
       "  158: '李想',\n",
       "  159: 'Chris Britt,\\xa0Ryan King',\n",
       "  160: 'Ingmar Hoerr',\n",
       "  161: 'Dave Palmer,\\xa0Emily Orton,\\xa0Jack Stockdale,\\xa0Nicole Eagan,\\xa0Poppy Gustafsson',\n",
       "  162: 'Jeff Kinsey,\\xa0Theodore Bailey',\n",
       "  163: 'Bhavesh Manglani,\\xa0Kapil Bharati,\\xa0Mohit Tandon,\\xa0Sahil Barua,\\xa0Suraj Saharan',\n",
       "  164: 'Greg Orlowski,\\xa0William Shu',\n",
       "  165: 'Chris Schuh,\\xa0Ely Sachs,\\xa0Emanuel M. Sachs,\\xa0John Hart,\\xa0Jonah Myerberg,\\xa0Ric Fulop,\\xa0Rick Chin,\\xa0Yet-Ming Chiang',\n",
       "  166: 'Ed Park,\\xa0Jeremy Delinsky,\\xa0Todd Park',\n",
       "  167: 'Dominic Williams',\n",
       "  168: 'Jason Citron',\n",
       "  169: 'André Schwämmlein,\\xa0Daniel Krauss,\\xa0Jochen Engert',\n",
       "  170: 'Girish Mathrubootham,\\xa0Shan Krishnasamy',\n",
       "  171: 'Dave Waiser,\\xa0Roi More',\n",
       "  172: 'Nigel Toon,\\xa0Simon Knowles',\n",
       "  173: 'Edward Kim,\\xa0Joshua Reeves,\\xa0Tomer London',\n",
       "  174: 'Armon Dadgar,\\xa0Mitchell Hashimoto',\n",
       "  175: 'Charles A. Taylor,\\xa0Christopher K. Zarins',\n",
       "  176: 'Monte Casino,\\xa0Patrick Brown',\n",
       "  177: 'Herman Narula,\\xa0Peter Lipka,\\xa0Rob Whitehead',\n",
       "  178: 'Moshe Yanai',\n",
       "  179: 'David Elkington,\\xa0Ken Krogue,\\xa0Rob Christensen',\n",
       "  180: 'Ben Nadel,\\xa0Clark Valberg',\n",
       "  181: '杨秋瑾',\n",
       "  182: 'Gerald Blackie',\n",
       "  183: '王育林',\n",
       "  184: 'Benny Landa',\n",
       "  185: 'Daniel Schreiber,\\xa0Shai Wininger',\n",
       "  186: 'Adam Zhang,\\xa0Brad Bao,\\xa0Charlie Gao,\\xa0Toby Sun',\n",
       "  187: '陈罡',\n",
       "  188: 'Jason Gardner',\n",
       "  189: '叶国富',\n",
       "  190: 'Eran Zinman,\\xa0Roy Mann',\n",
       "  191: 'Michael A Liberty',\n",
       "  192: 'Dhiraj C Rajaram',\n",
       "  193: 'Patrick Soon-Shiong',\n",
       "  194: 'Adam Ginsburg,\\xa0David Wiesen,\\xa0Madison Bell,\\xa0Nirav Tolia,\\xa0Prakash Janakiraman,\\xa0Sarah Leary',\n",
       "  195: 'Craig Weiss',\n",
       "  196: 'Paolo Cerruti,\\xa0Peter Carlsson',\n",
       "  197: 'Gordon Sanghera,\\xa0Hagan Bayley',\n",
       "  198: 'Adam Bowen,\\xa0James Monsees',\n",
       "  199: '陈宇',\n",
       "  200: '彭军 、楼天城',\n",
       "  201: 'Bastian Lehmann,\\xa0Sam Street,\\xa0Sean Plaice',\n",
       "  202: 'Daisuke Okanohara,\\xa0Toru Nishikawa',\n",
       "  203: 'Louay Eldada,\\xa0Yu Tianyue',\n",
       "  204: 'Adam D’Angelo,\\xa0Charlie Cheever',\n",
       "  205: '汪莹',\n",
       "  206: 'Sumant Sinha',\n",
       "  207: 'Nikolay Storonsky,\\xa0Vlad Yatsenko',\n",
       "  208: 'Calvin French-Owen,\\xa0Ian Storm Taylor,\\xa0Ilya Volodarsky,\\xa0Peter Reinhardt',\n",
       "  209: 'Ara Mahdessian,\\xa0Vahe Kuzoyan',\n",
       "  210: 'Jeff Arnold,\\xa0Mehmet Oz',\n",
       "  211: 'Ragy Thomas',\n",
       "  212: 'Anthony Casalena',\n",
       "  213: 'Robert Simonds,\\xa0William McGlashan',\n",
       "  214: '张近东',\n",
       "  215: '俞永福',\n",
       "  216: 'Bradley Keywell',\n",
       "  217: 'Andrew Hunt,\\xa0David Gilboa,\\xa0Jeffrey Raider,\\xa0Neil Blumenthal',\n",
       "  218: '朱珑',\n",
       "  219: 'Laks Srini,\\xa0Parker Conrad',\n",
       "  220: '周源',\n",
       "  221: 'Cyrus Massoumi,\\xa0Nick Ganju,\\xa0Oliver Kharraz',\n",
       "  222: 'Alex Garden,\\xa0Julia Collins',\n",
       "  223: '谷峰',\n",
       "  224: '刘金良',\n",
       "  225: '沈博阳',\n",
       "  226: '胡东',\n",
       "  227: '张海亮',\n",
       "  228: '谭龙',\n",
       "  229: '李锋',\n",
       "  230: '应书岭',\n",
       "  231: '张一春',\n",
       "  232: '李檬',\n",
       "  233: '刘天文',\n",
       "  234: '辛利军',\n",
       "  235: '何力',\n",
       "  236: '汪建国',\n",
       "  237: '王志豪',\n",
       "  238: '洪清华',\n",
       "  239: '刘楠',\n",
       "  240: '葛岚',\n",
       "  241: '姬晓晨',\n",
       "  242: '朱一闻',\n",
       "  243: '高禄峰',\n",
       "  244: '田宁',\n",
       "  245: '李建全',\n",
       "  246: '解居志',\n",
       "  247: '许仰天',\n",
       "  248: '张勇',\n",
       "  249: '黄宏生',\n",
       "  250: '居静',\n",
       "  251: '蒋韬',\n",
       "  252: '王国彬',\n",
       "  253: '陈敏',\n",
       "  254: '罗军',\n",
       "  255: '王学集',\n",
       "  256: '王珂',\n",
       "  257: '黎瑞刚',\n",
       "  258: '李革',\n",
       "  259: '陈驰',\n",
       "  260: '张继学',\n",
       "  261: '朱明跃',\n",
       "  262: '王东',\n",
       "  263: '张韶峰',\n",
       "  264: 'Ben Hindson,\\xa0Serge Saxonov',\n",
       "  265: '刘畅',\n",
       "  266: '杨陵江',\n",
       "  267: '戴文渊',\n",
       "  268: '孙雷',\n",
       "  269: 'Sebastian Betz,\\xa0Tarek Muller',\n",
       "  270: 'Ash Ashutosh,\\xa0David Chang',\n",
       "  271: 'Doug Dohring',\n",
       "  272: 'Andrew Ofstad,\\xa0Emmett Nicholas,\\xa0Howie Liu',\n",
       "  273: 'Jack Zhang',\n",
       "  274: '李文博',\n",
       "  275: '张勇',\n",
       "  276: 'Joseph Zwillinger,\\xa0Tim Brown',\n",
       "  277: 'Robert Edward Grant',\n",
       "  278: '王拥军',\n",
       "  279: '吉朋松',\n",
       "  280: 'Daniel Saks,\\xa0Nicolas Desmarais',\n",
       "  281: 'Eugenio Pace,\\xa0Matias Woloski',\n",
       "  282: 'Matt Mullenweg',\n",
       "  283: 'Michael Praeger',\n",
       "  284: 'Jen Rubio,\\xa0Steph Korey',\n",
       "  285: '郝飞',\n",
       "  286: '张良伦',\n",
       "  287: 'Abhinay Choudhari,\\xa0Hari Menon,\\xa0Vipul Parekh,\\xa0VS Sudhakar',\n",
       "  288: 'René Lacerte',\n",
       "  289: 'Valery Nebesny,\\xa0Valery Vavilov',\n",
       "  290: 'Markus Villig,\\xa0Martin Villig,\\xa0Oliver Leisalu',\n",
       "  291: '唐颖之',\n",
       "  292: '黄希鸣',\n",
       "  293: 'Alex Austin,\\xa0Dmitri Gaskin,\\xa0Mada Seghete,\\xa0Mike Molinet',\n",
       "  294: 'Achmad Zaky,\\xa0Nugroho Herucahyono',\n",
       "  295: 'Jonathan M. Rothberg,\\xa0Nevada Sanchez,\\xa0Tyler S. Ralston',\n",
       "  296: 'Patricia House,\\xa0Thomas Siebel',\n",
       "  297: 'Adrian Merino,\\xa0Francisco Montero,\\xa0Juan De Antonio,\\xa0Sam Lown,\\xa0Vicente Pascual',\n",
       "  298: 'Alex Tew,\\xa0Michael Acton Smith',\n",
       "  299: '商宝国',\n",
       "  300: 'Constantin Eis,\\xa0Gabriel Flateman,\\xa0Jeff Chapin,\\xa0Neil Parikh,\\xa0Philip Krim,\\xa0T. Luke Sherwin',\n",
       "  301: 'Alexander Rinke,\\xa0Bastian Nominacher,\\xa0Martin Klenk',\n",
       "  302: 'Dave Baxter,\\xa0Harjinder S. Bhade,\\xa0Milton T. Tormey,\\xa0Praveen Mandal,\\xa0Richard Lowenthal',\n",
       "  303: '黄巍',\n",
       "  304: '黄乐',\n",
       "  305: '李光辉',\n",
       "  306: 'Lee Holloway,\\xa0Matthew Prince,\\xa0Michelle Zatlyn',\n",
       "  307: 'Kris Gale,\\xa0Vivek Garipalli',\n",
       "  308: 'Mohit Aron',\n",
       "  309: 'Felix Van De Maele,\\xa0Pieter De Leenheer,\\xa0Stijn Christiaens',\n",
       "  310: 'Dror Erez,\\xa0Gaby Bilczyk,\\xa0Ronen Shilo',\n",
       "  311: 'Dan Lewis,\\xa0Grant Goodale',\n",
       "  312: 'Andrew Ng,\\xa0Daphne Koller',\n",
       "  313: '郅慧',\n",
       "  314: '姚劲波',\n",
       "  315: 'Jeremy Achin,\\xa0Thomas DeGodoy',\n",
       "  316: 'Bruce Journey,\\xa0Mike Baker,\\xa0Sandro Catanzaro,\\xa0Willard Simmons',\n",
       "  317: 'Daniel Marhely,\\xa0Jonathan Benassaya',\n",
       "  318: '苏海德',\n",
       "  319: 'Solomon Hykes',\n",
       "  320: 'Franck Tetzlaff,\\xa0Ivan Schneider,\\xa0Jessy Bernal,\\xa0Stanislas Niox-Chateau,\\xa0Steve Abou Rjeily,\\xa0Thomas Landais',\n",
       "  321: '石一',\n",
       "  322: 'Jason Robins,\\xa0Matt Kalish,\\xa0Paul Liberman',\n",
       "  323: 'Harsh Jain',\n",
       "  324: 'Jaspreet Singh,\\xa0Milind Borate,\\xa0Ramani Kothandaraman',\n",
       "  325: '吴敬传',\n",
       "  326: '李天天',\n",
       "  327: '刘江涛',\n",
       "  328: '张雷',\n",
       "  329: 'Phil Libin,\\xa0Stepan Pachikov',\n",
       "  330: 'Briscoe Rodgers,\\xa0Stefania Mallett',\n",
       "  331: 'Boone Park,\\xa0Craig Nehamen,\\xa0Georg Bauer,\\xa0Jennifer Parke,\\xa0Matt Cacciola,\\xa0Scott Painter',\n",
       "  332: '段毅',\n",
       "  333: '葛永昌',\n",
       "  334: '徐育斌',\n",
       "  335: 'David Cranor,\\xa0Maxim Lobovsky,\\xa0Natan Linder',\n",
       "  336: '罗旭',\n",
       "  337: '翟学魂',\n",
       "  338: '崔晶晶',\n",
       "  339: 'Jochen Mattes,\\xa0Johannes Reck,\\xa0Martin Sieber,\\xa0Pascal Mathis,\\xa0Tao Tao,\\xa0Tobias Rein',\n",
       "  340: 'Austin Che,\\xa0Barry Canton,\\xa0Jason Kelly,\\xa0Reshma Shetty,\\xa0Tom Knight',\n",
       "  341: 'Dmitriy Zaporozhets,\\xa0Sytse Sijbrandij',\n",
       "  342: '-',\n",
       "  343: 'Emily Weiss',\n",
       "  344: 'Cesar Carvalho, Joao Barbosa',\n",
       "  345: '王航',\n",
       "  346: 'Steven Barlow,\\xa0Thomas Burton',\n",
       "  347: 'Kavin Bharti Mittal',\n",
       "  348: 'Andrew Dudum,\\xa0Jack Abraham',\n",
       "  349: 'Jean-Francois Baril',\n",
       "  350: '汪建国',\n",
       "  351: '张勇',\n",
       "  352: '许广彬',\n",
       "  353: '方业昌',\n",
       "  354: '伏彩瑞',\n",
       "  355: 'J. Venter,\\xa0Peter Diamandis,\\xa0Robert Hariri',\n",
       "  356: '王俊',\n",
       "  357: 'Monish Darda, Samir Bodas',\n",
       "  358: 'Eduardo Baer,\\xa0Felipe Ramos Fioravante,\\xa0Gabriel Pinto,\\xa0Guilherme Bonifacio,\\xa0Patrick Sigrist',\n",
       "  359: '潘定国',\n",
       "  360: 'Andrew Rubin,\\xa0PJ Kirner',\n",
       "  361: 'Abhay Singhal,\\xa0Amit Gupta,\\xa0Mohit Saxena,\\xa0Naveen Tewari,\\xa0Piyush Shah',\n",
       "  362: 'Ciaran Lee,\\xa0David Barrett,\\xa0Des Traynor,\\xa0Eoghan McCabe',\n",
       "  363: '江建飞',\n",
       "  364: 'Arnon Harish,\\xa0Eyal Milrad,\\xa0Gil Shoham,\\xa0Itay Milrad,\\xa0Nethanel Shadmi,\\xa0Omer Kaplan,\\xa0Roi Milrad,\\xa0Tamir Carmi,\\xa0Tomer Bar Zeev,\\xa0Tomer Bar Zeev',\n",
       "  365: '杨正大',\n",
       "  366: 'David Khuat-Duy',\n",
       "  367: 'Frederic Simon,\\xa0Shlomi Ben Haim,\\xa0Yoav Landman',\n",
       "  368: '郝鸿峰',\n",
       "  369: '李海燕',\n",
       "  370: '黄承松',\n",
       "  371: '白如冰',\n",
       "  372: '王叁寿',\n",
       "  373: 'Kathryn Petralia,\\xa0Marc Gorlin,\\xa0Rob Frohwein',\n",
       "  374: 'Obaid Khan,\\xa0Ryan Johns,\\xa0Shoaib Makani',\n",
       "  375: 'Kendra Scott',\n",
       "  376: 'Stu Sjouwerman',\n",
       "  377: '刘夜',\n",
       "  378: '刘成城',\n",
       "  379: '周胜馥',\n",
       "  380: '金赞',\n",
       "  381: '朱江明',\n",
       "  382: 'Alec Oxenford,\\xa0Enrique Linares Plaza,\\xa0Jordi Castello',\n",
       "  383: '章征宇',\n",
       "  384: 'Amit Goldstein,\\xa0Itai Tsiddon,\\xa0Nir Pochter,\\xa0Yaron Inger,\\xa0Zeev Farbman',\n",
       "  385: '张天泽',\n",
       "  386: '宋群',\n",
       "  387: '苏晓',\n",
       "  388: 'Mike Kayamori',\n",
       "  389: 'Arthur Debert,\\xa0Eduardo Wexler,\\xa0Fabien Mendez',\n",
       "  390: '宋睿',\n",
       "  391: 'James Burgess,\\xa0John Hering,\\xa0Kevin Mahaffey',\n",
       "  392: '罗振宇',\n",
       "  393: '林凡',\n",
       "  394: 'Christopher Lindblad,\\xa0Frank R. Caufield,\\xa0Paul Pedersen',\n",
       "  395: 'Erich Wasserman,\\xa0Greg Williams,\\xa0Joe Zawadzki,\\xa0Srinath Gaddam',\n",
       "  396: 'Thomas Rebaud',\n",
       "  397: 'Benjamin Hindman,\\xa0Florian Leibert,\\xa0Tobi Knaup',\n",
       "  398: '何涛',\n",
       "  399: 'Xiao Diaokun,LI Xiang,\\xa0Wu Yang',\n",
       "  400: 'Tej Tadi',\n",
       "  401: '吴明辉',\n",
       "  402: '李志飞',\n",
       "  403: '曹旭东',\n",
       "  404: 'Chee Mun Foong,\\xa0Diwakar Choubey,\\xa0Pratyush Tiwari',\n",
       "  405: 'Sanjay Beri',\n",
       "  406: '-',\n",
       "  407: '陈浩',\n",
       "  408: '李瑞强',\n",
       "  409: 'Arean van Veelen,\\xa0Nick Huzar',\n",
       "  410: 'Anand Shah,\\xa0Ankit Jain',\n",
       "  411: 'Naren Shaam',\n",
       "  412: 'Tom X. Lee, MD',\n",
       "  413: 'Kabir Barday',\n",
       "  414: '黄源浩',\n",
       "  415: 'Amnon Shashua,\\xa0Ziv Aviram',\n",
       "  416: 'Andrew Kinzer,\\xa0Gordon Hempton,\\xa0Manny Medina,\\xa0Wes Hather',\n",
       "  417: 'Paulo Rosado,\\xa0Rui Pereira',\n",
       "  418: 'Stephen Fitzpatrick',\n",
       "  419: 'Ari Ojalvo,\\xa0Umut Tekin',\n",
       "  420: 'Pat McGrath',\n",
       "  421: '杨冰',\n",
       "  422: 'Alok Bansal,\\xa0Yashish Dahiya',\n",
       "  423: '楊思枏',\n",
       "  424: 'Andrew Thompson,\\xa0George Savage,\\xa0Mark Zdeblick',\n",
       "  425: 'Pranay Chulet, Jiby Thomas',\n",
       "  426: 'George Bousis',\n",
       "  427: 'Felipe Villamarin,\\xa0Sebastian Mejia,\\xa0Simon Borrero',\n",
       "  428: '李健',\n",
       "  429: '杨一夫',\n",
       "  430: 'Jennifer Fleiss,\\xa0Jennifer Hyman',\n",
       "  431: 'Robbie Antonio',\n",
       "  432: 'Deepak Garg,\\xa0Gazal Kalra',\n",
       "  433: 'Peter Beck',\n",
       "  434: 'Alex Timm,\\xa0Dan Manges',\n",
       "  435: 'Lane B. Moore,\\xa0Marc Spiegel,\\xa0Nate Morris,\\xa0Perry Moss',\n",
       "  436: 'Rich Mahoney',\n",
       "  437: 'Radhika Aggarwal,\\xa0Sandeep Aggarwal,\\xa0Sanjay Sethi',\n",
       "  438: '魏东',\n",
       "  439: '沈鹏',\n",
       "  440: 'Alex Jacobs,\\xa0Gene Berdichevsky,\\xa0Gleb Yushin',\n",
       "  441: '谢良志',\n",
       "  442: '苏峻',\n",
       "  443: 'Francis Davidson, Lucas Pellan, Olivier Gareau',\n",
       "  444: 'James Hom,\\xa0Keyvan Mohajer,\\xa0Majid Emami',\n",
       "  445: 'Dan Gilbert,\\xa0Josh Luber',\n",
       "  446: 'Christian Beedgen',\n",
       "  447: 'Jonathan Neman,\\xa0Nathaniel Ru,\\xa0Nicolas Jammet',\n",
       "  448: 'David Gurle',\n",
       "  449: 'Adam Singolda',\n",
       "  450: 'Cristina Fonseca,\\xa0Tiago Paiva',\n",
       "  451: '崔晓波',\n",
       "  452: 'Eric Setton,\\xa0Uri Raz',\n",
       "  453: 'Adam Goldenberg,\\xa0Don Ressler',\n",
       "  454: '王仕锐',\n",
       "  455: 'Brian Lee,\\xa0Christopher Gavigan,\\xa0Jessica Alba,\\xa0Sean Kane',\n",
       "  456: 'Abhishek Rai,\\xa0Ajeet Singh,\\xa0Amit Prakash,\\xa0Priyendra Deshwal,\\xa0Sanjay Agrawal,\\xa0Shashank Gupta,\\xa0Vijay Ganesan',\n",
       "  457: 'Jeremy Tunnell,\\xa0Jonathan Swanson,\\xa0Marco Zappacosta,\\xa0Sander Daniels',\n",
       "  458: 'Christopher Cynn,\\xa0Daniel Shin,\\xa0Kihyun Kwon,\\xa0Tommy Donghyun Kim',\n",
       "  459: 'Seunggun Lee',\n",
       "  460: 'Christian Lanng,\\xa0Gert Sylvest,\\xa0Mikkel Brun',\n",
       "  461: 'Abhishek Virendra Mehta,\\xa0Richard Morris',\n",
       "  462: 'Shelby Clark',\n",
       "  463: '郝佳男、陈默、侯晓迪',\n",
       "  464: '季昕华',\n",
       "  465: 'Amod Malviya,\\xa0Sujeet kumar,\\xa0Vaibhav Gupta',\n",
       "  466: 'David Stavens,\\xa0Mike Sokolsky,\\xa0Sebastian Thrun',\n",
       "  467: '梁家恩',\n",
       "  468: '周君强',\n",
       "  469: 'Paul Nguyen',\n",
       "  470: 'Craig Ramsey,\\xa0David Schmaier,\\xa0James Ramsey,\\xa0Mark Armenante,\\xa0Young Sohn',\n",
       "  471: 'Jerome Armstrong,\\xa0Joshua Topolsky,\\xa0Markos Moulitsas,\\xa0Tyler Bleszinski',\n",
       "  472: 'Brandon Weber,\\xa0Donald DeSantis,\\xa0Karl Baum,\\xa0Niall Smart,\\xa0Nicholas Romito,\\xa0Ryan Masiello',\n",
       "  473: '李治国',\n",
       "  474: 'Dan Adika,\\xa0Eyal Cohen,\\xa0Rephael Sweary',\n",
       "  475: '龙沛智',\n",
       "  476: '陈大年',\n",
       "  477: '张东风',\n",
       "  478: '谢旭辉',\n",
       "  479: 'Lee Sujin',\n",
       "  480: '丁根芳',\n",
       "  481: '张泉',\n",
       "  482: '李亚',\n",
       "  483: '王朝成',\n",
       "  484: '杨兴运',\n",
       "  485: '曾碧波',\n",
       "  486: '吴逸然',\n",
       "  487: '周枫',\n",
       "  488: '韩毅',\n",
       "  489: 'David A. Steinberg,\\xa0John Sculley',\n",
       "  490: '张翼',\n",
       "  491: '姚劲波',\n",
       "  492: 'Keenan Wyrobek,\\xa0Keller Rinaudo,\\xa0Will Hetzler',\n",
       "  493: 'Ian Siegel,\\xa0Joe Edmonds,\\xa0Ward Poulos,\\xa0Willis Redd'},\n",
       " '成立年份': {0: 2014,\n",
       "  1: 2012,\n",
       "  2: 2012,\n",
       "  3: 2002,\n",
       "  4: 2015,\n",
       "  5: 2008,\n",
       "  6: 2011,\n",
       "  7: 2002,\n",
       "  8: 2010,\n",
       "  9: 2010,\n",
       "  10: 2014,\n",
       "  11: 2013,\n",
       "  12: 2013,\n",
       "  13: 2011,\n",
       "  14: 2006,\n",
       "  15: 2012,\n",
       "  16: 2007,\n",
       "  17: 2004,\n",
       "  18: 2013,\n",
       "  19: 2013,\n",
       "  20: 2007,\n",
       "  21: 2008,\n",
       "  22: 2010,\n",
       "  23: 2010,\n",
       "  24: 2018,\n",
       "  25: 2011,\n",
       "  26: 2010,\n",
       "  27: 2016,\n",
       "  28: 2010,\n",
       "  29: 2012,\n",
       "  30: 2016,\n",
       "  31: 2012,\n",
       "  32: 2013,\n",
       "  33: 2016,\n",
       "  34: 2014,\n",
       "  35: 2015,\n",
       "  36: 2014,\n",
       "  37: 2006,\n",
       "  38: 2007,\n",
       "  39: 2009,\n",
       "  40: 2015,\n",
       "  41: 2005,\n",
       "  42: 2008,\n",
       "  43: 2014,\n",
       "  44: 2011,\n",
       "  45: 2010,\n",
       "  46: 2014,\n",
       "  47: 2015,\n",
       "  48: 2010,\n",
       "  49: 2007,\n",
       "  50: 2012,\n",
       "  51: 2008,\n",
       "  52: 2013,\n",
       "  53: 2012,\n",
       "  54: 2009,\n",
       "  55: 2004,\n",
       "  56: 2012,\n",
       "  57: 2012,\n",
       "  58: 2007,\n",
       "  59: 2014,\n",
       "  60: 2009,\n",
       "  61: 2014,\n",
       "  62: 2005,\n",
       "  63: 2011,\n",
       "  64: 2014,\n",
       "  65: 2010,\n",
       "  66: 2013,\n",
       "  67: 2014,\n",
       "  68: 2010,\n",
       "  69: 2012,\n",
       "  70: 2015,\n",
       "  71: 2012,\n",
       "  72: 2011,\n",
       "  73: 2011,\n",
       "  74: 2012,\n",
       "  75: 2015,\n",
       "  76: 2012,\n",
       "  77: 2010,\n",
       "  78: 2015,\n",
       "  79: 2014,\n",
       "  80: 2011,\n",
       "  81: 2008,\n",
       "  82: 2011,\n",
       "  83: 2012,\n",
       "  84: 2003,\n",
       "  85: 2003,\n",
       "  86: 2017,\n",
       "  87: 2013,\n",
       "  88: 2012,\n",
       "  89: 2002,\n",
       "  90: 2013,\n",
       "  91: 2015,\n",
       "  92: 2014,\n",
       "  93: 2006,\n",
       "  94: 2013,\n",
       "  95: 2014,\n",
       "  96: 2018,\n",
       "  97: 2013,\n",
       "  98: 2011,\n",
       "  99: 2016,\n",
       "  100: 2009,\n",
       "  101: 2012,\n",
       "  102: 2015,\n",
       "  103: 2008,\n",
       "  104: 2015,\n",
       "  105: 2007,\n",
       "  106: 2014,\n",
       "  107: 2015,\n",
       "  108: 2013,\n",
       "  109: 2016,\n",
       "  110: 2013,\n",
       "  111: 2012,\n",
       "  112: 2012,\n",
       "  113: 2010,\n",
       "  114: 2012,\n",
       "  115: 2002,\n",
       "  116: 2015,\n",
       "  117: 2005,\n",
       "  118: 2004,\n",
       "  119: 2014,\n",
       "  120: 2014,\n",
       "  121: 2013,\n",
       "  122: 2012,\n",
       "  123: 2014,\n",
       "  124: 2015,\n",
       "  125: 2011,\n",
       "  126: 2004,\n",
       "  127: 2015,\n",
       "  128: 2013,\n",
       "  129: 2011,\n",
       "  130: 2013,\n",
       "  131: 2005,\n",
       "  132: 2013,\n",
       "  133: 2014,\n",
       "  134: 2012,\n",
       "  135: 2014,\n",
       "  136: 2014,\n",
       "  137: 2006,\n",
       "  138: 2006,\n",
       "  139: 2010,\n",
       "  140: 2012,\n",
       "  141: 2014,\n",
       "  142: 2008,\n",
       "  143: 2016,\n",
       "  144: 2012,\n",
       "  145: 2013,\n",
       "  146: 2000,\n",
       "  147: 2017,\n",
       "  148: 2017,\n",
       "  149: 2006,\n",
       "  150: 2017,\n",
       "  151: 2006,\n",
       "  152: 2017,\n",
       "  153: 2016,\n",
       "  154: 2006,\n",
       "  155: 2013,\n",
       "  156: 2012,\n",
       "  157: 2012,\n",
       "  158: 2015,\n",
       "  159: 2013,\n",
       "  160: 2000,\n",
       "  161: 2013,\n",
       "  162: 2009,\n",
       "  163: 2011,\n",
       "  164: 2012,\n",
       "  165: 2015,\n",
       "  166: 2017,\n",
       "  167: 2015,\n",
       "  168: 2012,\n",
       "  169: 2011,\n",
       "  170: 2010,\n",
       "  171: 2010,\n",
       "  172: 2016,\n",
       "  173: 2011,\n",
       "  174: 2012,\n",
       "  175: 2009,\n",
       "  176: 2011,\n",
       "  177: 2012,\n",
       "  178: 2011,\n",
       "  179: 2004,\n",
       "  180: 2011,\n",
       "  181: 2010,\n",
       "  182: 2000,\n",
       "  183: 2011,\n",
       "  184: 2002,\n",
       "  185: 2015,\n",
       "  186: 2017,\n",
       "  187: 2006,\n",
       "  188: 2010,\n",
       "  189: 2013,\n",
       "  190: 2012,\n",
       "  191: 2008,\n",
       "  192: 2004,\n",
       "  193: 2012,\n",
       "  194: 2010,\n",
       "  195: 2006,\n",
       "  196: 2016,\n",
       "  197: 2005,\n",
       "  198: 2017,\n",
       "  199: 2015,\n",
       "  200: 2016,\n",
       "  201: 2011,\n",
       "  202: 2014,\n",
       "  203: 2012,\n",
       "  204: 2009,\n",
       "  205: 2018,\n",
       "  206: 2011,\n",
       "  207: 2015,\n",
       "  208: 2011,\n",
       "  209: 2013,\n",
       "  210: 2010,\n",
       "  211: 2009,\n",
       "  212: 2003,\n",
       "  213: 2014,\n",
       "  214: 2015,\n",
       "  215: 2014,\n",
       "  216: 2014,\n",
       "  217: 2010,\n",
       "  218: 2012,\n",
       "  219: 2013,\n",
       "  220: 2011,\n",
       "  221: 2007,\n",
       "  222: 2015,\n",
       "  223: 2017,\n",
       "  224: 2015,\n",
       "  225: 2015,\n",
       "  226: 2013,\n",
       "  227: 2017,\n",
       "  228: 2012,\n",
       "  229: 2006,\n",
       "  230: 2015,\n",
       "  231: 2013,\n",
       "  232: 2009,\n",
       "  233: 2001,\n",
       "  234: 2019,\n",
       "  235: 2014,\n",
       "  236: 2009,\n",
       "  237: 2014,\n",
       "  238: 2008,\n",
       "  239: 2011,\n",
       "  240: 2010,\n",
       "  241: 2009,\n",
       "  242: 2013,\n",
       "  243: 2013,\n",
       "  244: 2004,\n",
       "  245: 2009,\n",
       "  246: 2000,\n",
       "  247: 2008,\n",
       "  248: 2011,\n",
       "  249: 2017,\n",
       "  250: 2015,\n",
       "  251: 2012,\n",
       "  252: 2008,\n",
       "  253: 2014,\n",
       "  254: 2011,\n",
       "  255: 2014,\n",
       "  256: 2011,\n",
       "  257: 2015,\n",
       "  258: 2015,\n",
       "  259: 2012,\n",
       "  260: 2013,\n",
       "  261: 2005,\n",
       "  262: 2012,\n",
       "  263: 2014,\n",
       "  264: 2012,\n",
       "  265: 2007,\n",
       "  266: 2006,\n",
       "  267: 2015,\n",
       "  268: 2006,\n",
       "  269: 2014,\n",
       "  270: 2009,\n",
       "  271: 2007,\n",
       "  272: 2012,\n",
       "  273: 2016,\n",
       "  274: 2015,\n",
       "  275: 2015,\n",
       "  276: 2015,\n",
       "  277: 2013,\n",
       "  278: 2010,\n",
       "  279: 2008,\n",
       "  280: 2009,\n",
       "  281: 2013,\n",
       "  282: 2005,\n",
       "  283: 2000,\n",
       "  284: 2015,\n",
       "  285: 2015,\n",
       "  286: 2014,\n",
       "  287: 2011,\n",
       "  288: 2006,\n",
       "  289: 2011,\n",
       "  290: 2013,\n",
       "  291: 2012,\n",
       "  292: 2017,\n",
       "  293: 2014,\n",
       "  294: 2011,\n",
       "  295: 2011,\n",
       "  296: 2009,\n",
       "  297: 2011,\n",
       "  298: 2012,\n",
       "  299: 2018,\n",
       "  300: 2013,\n",
       "  301: 2011,\n",
       "  302: 2007,\n",
       "  303: 2012,\n",
       "  304: 2010,\n",
       "  305: 2011,\n",
       "  306: 2009,\n",
       "  307: 2013,\n",
       "  308: 2013,\n",
       "  309: 2008,\n",
       "  310: 2010,\n",
       "  311: 2015,\n",
       "  312: 2012,\n",
       "  313: 2013,\n",
       "  314: 2014,\n",
       "  315: 2012,\n",
       "  316: 2009,\n",
       "  317: 2006,\n",
       "  318: 2012,\n",
       "  319: 2010,\n",
       "  320: 2013,\n",
       "  321: 2015,\n",
       "  322: 2012,\n",
       "  323: 2012,\n",
       "  324: 2008,\n",
       "  325: 2015,\n",
       "  326: 2000,\n",
       "  327: 2011,\n",
       "  328: 2008,\n",
       "  329: 2000,\n",
       "  330: 2007,\n",
       "  331: 2016,\n",
       "  332: 2011,\n",
       "  333: 2007,\n",
       "  334: 2015,\n",
       "  335: 2011,\n",
       "  336: 2011,\n",
       "  337: 2011,\n",
       "  338: 2012,\n",
       "  339: 2009,\n",
       "  340: 2009,\n",
       "  341: 2014,\n",
       "  342: 2014,\n",
       "  343: 2014,\n",
       "  344: 2012,\n",
       "  345: 2006,\n",
       "  346: 2008,\n",
       "  347: 2012,\n",
       "  348: 2017,\n",
       "  349: 2016,\n",
       "  350: 2009,\n",
       "  351: 2014,\n",
       "  352: 2010,\n",
       "  353: 2010,\n",
       "  354: 2001,\n",
       "  355: 2013,\n",
       "  356: 2015,\n",
       "  357: 2009,\n",
       "  358: 2011,\n",
       "  359: 2014,\n",
       "  360: 2013,\n",
       "  361: 2007,\n",
       "  362: 2011,\n",
       "  363: 2013,\n",
       "  364: 2010,\n",
       "  365: 2008,\n",
       "  366: 2000,\n",
       "  367: 2008,\n",
       "  368: 2010,\n",
       "  369: 2012,\n",
       "  370: 2012,\n",
       "  371: 2011,\n",
       "  372: 2010,\n",
       "  373: 2009,\n",
       "  374: 2013,\n",
       "  375: 2002,\n",
       "  376: 2010,\n",
       "  377: 2014,\n",
       "  378: 2016,\n",
       "  379: 2013,\n",
       "  380: 2011,\n",
       "  381: 2017,\n",
       "  382: 2015,\n",
       "  383: 2009,\n",
       "  384: 2013,\n",
       "  385: 2014,\n",
       "  386: 2016,\n",
       "  387: 2014,\n",
       "  388: 2014,\n",
       "  389: 2013,\n",
       "  390: 2014,\n",
       "  391: 2007,\n",
       "  392: 2012,\n",
       "  393: 2012,\n",
       "  394: 2001,\n",
       "  395: 2007,\n",
       "  396: 2016,\n",
       "  397: 2013,\n",
       "  398: 2015,\n",
       "  399: 2006,\n",
       "  400: 2012,\n",
       "  401: 2014,\n",
       "  402: 2012,\n",
       "  403: 2016,\n",
       "  404: 2013,\n",
       "  405: 2012,\n",
       "  406: 2015,\n",
       "  407: 2017,\n",
       "  408: 2011,\n",
       "  409: 2011,\n",
       "  410: 2017,\n",
       "  411: 2012,\n",
       "  412: 2007,\n",
       "  413: 2019,\n",
       "  414: 2013,\n",
       "  415: 2010,\n",
       "  416: 2013,\n",
       "  417: 2001,\n",
       "  418: 2009,\n",
       "  419: 2013,\n",
       "  420: 2015,\n",
       "  421: 2015,\n",
       "  422: 2008,\n",
       "  423: 2006,\n",
       "  424: 2001,\n",
       "  425: 2008,\n",
       "  426: 2013,\n",
       "  427: 2016,\n",
       "  428: 2014,\n",
       "  429: 2010,\n",
       "  430: 2009,\n",
       "  431: 2015,\n",
       "  432: 2014,\n",
       "  433: 2006,\n",
       "  434: 2015,\n",
       "  435: 2008,\n",
       "  436: 2016,\n",
       "  437: 2011,\n",
       "  438: 2015,\n",
       "  439: 2016,\n",
       "  440: 2011,\n",
       "  441: 2007,\n",
       "  442: 2014,\n",
       "  443: 2012,\n",
       "  444: 2005,\n",
       "  445: 2015,\n",
       "  446: 2010,\n",
       "  447: 2007,\n",
       "  448: 2014,\n",
       "  449: 2007,\n",
       "  450: 2011,\n",
       "  451: 2011,\n",
       "  452: 2009,\n",
       "  453: 2010,\n",
       "  454: 2018,\n",
       "  455: 2012,\n",
       "  456: 2012,\n",
       "  457: 2008,\n",
       "  458: 2010,\n",
       "  459: 2011,\n",
       "  460: 2009,\n",
       "  461: 2011,\n",
       "  462: 2009,\n",
       "  463: 2015,\n",
       "  464: 2012,\n",
       "  465: 2016,\n",
       "  466: 2011,\n",
       "  467: 2012,\n",
       "  468: 2011,\n",
       "  469: 2007,\n",
       "  470: 2014,\n",
       "  471: 2003,\n",
       "  472: 2012,\n",
       "  473: 2009,\n",
       "  474: 2011,\n",
       "  475: 2013,\n",
       "  476: 2013,\n",
       "  477: 2009,\n",
       "  478: 2013,\n",
       "  479: 2005,\n",
       "  480: 2011,\n",
       "  481: 2012,\n",
       "  482: 2012,\n",
       "  483: 2014,\n",
       "  484: 2015,\n",
       "  485: 2009,\n",
       "  486: 2012,\n",
       "  487: 2007,\n",
       "  488: 2014,\n",
       "  489: 2007,\n",
       "  490: 2014,\n",
       "  491: 2015,\n",
       "  492: 2014,\n",
       "  493: 2010},\n",
       " '部分投资机构': {0: '春华资本、中投海外、红杉资本',\n",
       "  1: '红杉资本、海纳亚洲、纪源资本、启明创投',\n",
       "  2: '腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本',\n",
       "  3: 'Golden Gate Capital,\\xa0Koch Equity Development',\n",
       "  4: 'M13, Timothy Davis, Evolution VC Partners, Tiger Global Management, Altria, Capital Re',\n",
       "  5: 'Tiger Global Management, Founders Fund, Y Combinator, Sequioa Capital, Andreessen Horowitz, Greylock Partners,',\n",
       "  6: '摩根士丹利、中银集团、国泰君安（香港）',\n",
       "  7: 'DFJ, Founders Fund, Google, Bank of America, Baillie Gifford',\n",
       "  8: 'Softbank, Hony Capital, Glade Brook Capital, Wellington Management, Benchmark',\n",
       "  9: 'CapitalG, Thrive Capital, Y Combinator, Sequoia Capital, General Catalyst, Founders Fund, Tiger Global Management',\n",
       "  10: '腾讯、华平投资、淡马锡',\n",
       "  11: 'GIC、淡马锡、春华资本',\n",
       "  12: '红杉资本、嘉实投资、中国太平',\n",
       "  13: '红杉资本、晨兴资本、百度、腾讯',\n",
       "  14: 'Accel、红杉资本、麦星投资',\n",
       "  15: 'Vertex Ventures, GGV Capital,Rheingau Founders, SoftBank, SoftBank Capital, Tiger Global Management, Didi Chuxing, HSBC, Emtek Group, Toyota Motor Corporation, Hyundai Motor Company, Yamaha Motor Co., Tokyo Century, Central Group of Company, SoftBank Investment Advisers, Invesco, Microsoft, Bookings Holdings,',\n",
       "  16: 'Time Warner, Walt Disney, Providence Equity Partners',\n",
       "  17: 'Founders Fund, Kortschak Investments',\n",
       "  18: 'Y Combinator, Sequoia Capital, Kleiner Perkins, Khosla Ventures, Tamasek Holdings, DST Global, Softbank Investment Advisors, Coatue Management, Dragoneer Investment Group',\n",
       "  19: '红杉资本、IDG、Crimson Ventures, 创新工场',\n",
       "  20: '高瓴资本、红杉资本、腾讯',\n",
       "  21: 'Starling Group,\\xa0Vickers Venture Partners',\n",
       "  22: 'Openspace Ventures, Kohlberg Kravis Roberts, Warburg Pincus, Tencent Holdings, Google, JD.com, PT. Astra International Tbk - TSO Salemba',\n",
       "  23: 'Alibaba Group, SoftBank, Berkshire Hathaway, Sapphire Ventures, Mountain Capital, Ant Financial',\n",
       "  24: '腾讯',\n",
       "  25: '红杉资本、今日资本、IDG、经纬中国',\n",
       "  26: 'SoftBank Investment Advisers, Altos Ventures, Sequoia Capital, BlackRock Private Equity Partners, Softbank, Maverick Ventures',\n",
       "  27: 'IDG、思佰益、软银海外',\n",
       "  28: 'Formation 8, GGV Capital, Founders Fund, DST Global, Temasek Holdings',\n",
       "  29: 'DFJ, Andreessen Horowitz, Tiger Global Management, IVP, Bank of Tokyo-Mitsubishi',\n",
       "  30: 'Illumina, ARCH Venture Partners, 6 Dimensions Capital, Ally Bridge Group, Hillhouse Capital Group\\xa0, HuangPu River Capital',\n",
       "  31: 'Y Combinator, Sequoia Capital, Kleiner Perkins, Andreessen Horowitz, Tiger Global Management, Coatue Management, D1 capital partners, Whole Foods Market',\n",
       "  32: 'Index Ventures, New Enterprise Associates, DST Global',\n",
       "  33: 'Volkswagen, Ford',\n",
       "  34: '顺为资本、纪源资本、真格基金',\n",
       "  35: 'IDG、思佰益',\n",
       "  36: 'Softbank Investment Advisors, QVT Financial, Viking Global Investors, Novaquest Capital Management, RTW Investments LLC',\n",
       "  37: '光大控股、深创投',\n",
       "  38: 'Andreessen Horowitz, Franklin Templeton Investments,\\xa0Geodesic Capital,\\xa0IVP (Institutional Venture Partners), TPG, TPG Growth, Wellington Management',\n",
       "  39: 'Indonusa Dwitama, East Ventures, CyberAgent Capital, Beenos Partners, Softbank Ventures Asia, SoftBank Telecom Corp, Softbank Investment Advsors',\n",
       "  40: 'Denso, Softbank Investment Advisors, Toyota Motor Corporation',\n",
       "  41: 'Earlybird Venture Capital, Capital G, Sequoia Capital, Coatue Management, Accel',\n",
       "  42: 'Aarin Capital, Sequoia Capital India, Chan Zuckerberg Initiative, Sofina, Verlinvest, Tencent Holdings, Naspers, General Atlantic, Qatar Investment Authority, Sovereign Wealth Funds',\n",
       "  43: '腾讯、红杉资本、光速中国、高瓴资本、云峰基金、纪源资本',\n",
       "  44: \"Tamasek Holdings, Alibaba Group, Google, Saudi Arabia's Public Investment Fund, NTT Docomo\",\n",
       "  45: 'Tiger Global Management, Hyundai Motor Company, Kia Motors, Sequoia Capital India, SoftBank Capital, DST Global, Baillie Gifford, Vanguard, Softbank, Falcon Edge Capital, Tekne Capital, Yes Bank, Sachin Bansal, Temasek Holdings, China Eurasian Economic Cooperation Fund, Eternal Yield International, Steadview Capital, Tencent Holdings, Sailing Capital',\n",
       "  46: '鼎晖投资、IDG、中金公司',\n",
       "  47: '云锋基金、云岭投资、中金公司',\n",
       "  48: '红杉资本、高盛、腾讯、启明创投、高瓴资本',\n",
       "  49: 'Tencent Holdings',\n",
       "  50: 'Alibaba Group, Temasek Holding, Tesco, Rocket Internet',\n",
       "  51: 'Y Combinator, Menlo Ventures, JP Morgan Partners',\n",
       "  52: 'Greenoaks Capital, SoftBank, SoftBank Investment Advisers, Huazhu Hotels Group, Grab, Didi Chuxing, Airbnb',\n",
       "  53: 'Core Innovation Capital, IDG Capital, Santander InnoVentures, SBI Investment',\n",
       "  54: 'Ford Motor Company, Amazon',\n",
       "  55: 'Artemis, Lewis Trust Group, Kohlberg Kravis Roberts, Balderton Capital, Merian Global Investors, William Currie Group',\n",
       "  56: 'DN Capital, Piton Capital, DST Global, Princeville Global, SoftBank Investment Advisers',\n",
       "  57: 'IVP (Institutional Venture Partners), Wellington Management, Fidelity, SoftBank Investment Advisers, Qatar Investment Authority',\n",
       "  58: 'QED Investors, Susquehanna Growth Equity, CapitalG, SV Angel, Silver Lake Partners',\n",
       "  59: 'Evergrande Health Industry Group, Birch Lake Partners',\n",
       "  60: 'Zeev Ventures, Sequoia Capital, GGV Capital, New Enterprise Associates, ICONIQ Capital',\n",
       "  61: 'Flagship Pioneering, Alaska Permanent Fund, Activant Capital, Investment Corporation of Dubai (ICD), Baillie Gifford',\n",
       "  62: 'Investment AB Öresund, Sequoia Capital, General Atlantic, Creandum, Anders Holch Povlsen, Visa, Permira, H&M, Snoop Dogg',\n",
       "  63: '创新工场、启明创投、联想之星、建银国际、蚂蚁金服 、纪源资本',\n",
       "  64: '红杉资本、DST、京东',\n",
       "  65: 'Alsop Louie Partners, Spark Capital, IVP (Institutional Venture Partners)',\n",
       "  66: 'Sequoia Capital, Tiger Global Management, Founders Fund, Goldman Sachs, DST Global, Fortress Investment Group, Tencent Holdings',\n",
       "  67: 'Khosla Ventures, GGV Capital, Access Technology Ventures, Norwest Venture Partners, Lennar Corporation, SoftBank Investment Advisers, General Atlantic',\n",
       "  68: 'Tiger Global Management, L Catterton, Fidelity, Kleiner Perkins, True Ventures, Wellington Management',\n",
       "  69: '中信产业基金、基石资本、IDG',\n",
       "  70: 'Andreessen Horowitz, General Catalyst',\n",
       "  71: 'Sutter Hill Ventures, Redpoint, Altimeter Capital, ICONIQ Capital, Sequoia Capital',\n",
       "  72: 'Baseline Ventures, Morgan Stanley, The Bancorp, East West Bank, Discovery Capital, Third Point Ventures, Softbank, Silver Lake Partners, Qatar Investment Authority',\n",
       "  73: 'Seedcamp, IA Ventures\\xa0, Valar Ventures, Index Ventures, Andreessen Horowitz, Baillie Gifford, IVP (Institutional Venture Partners)\\xa0, JP Morgan, Lead Edge Capital, Merian Global Investors, LHV Ventures, NatWest Bank, Lone Pine Capital, Vitruvian Partners',\n",
       "  74: 'East Ventures, Global Founders Capital, GIC, Expedia',\n",
       "  75: 'Zeev Ventures, Lightspeed Venture Partners, Andreessen Horowitz, Gorup11',\n",
       "  76: '启明创投、科大讯飞、鼎晖投资、腾讯',\n",
       "  77: '中国人寿、国投创新',\n",
       "  78: '远景能源、红杉资本、海纳亚洲',\n",
       "  79: '晨兴资本、IDG、经纬中国、顺为资本、阿里巴巴、纪源资本',\n",
       "  80: '华平投资、红杉资本、腾讯',\n",
       "  81: 'Info Edge, Sequoia Capital, Vy Capital, Temasek Holdings, Sequoia Capital India, Ant Financial, Glade Brook Capital Partners, Delivery Hero',\n",
       "  82: 'General Atlantic, SoftBank Investment Advisers',\n",
       "  83: 'Spark Capital, Founders Capital, Morgan Stanley, GIC, Thrive Capital, HVF Labs',\n",
       "  84: 'Goldman Sachs, SoftBank Investment Advisers, Workday Ventures',\n",
       "  85: '红杉资本、海纳亚洲、经纬中国、阿里巴巴、万达院线、腾讯',\n",
       "  86: 'Y Combinator, Ribbit Capital, DST Global, Barclays Investment Bank, Kleiner Perkins , Greenoaks Capital',\n",
       "  87: '锦江集团、暾澜资本',\n",
       "  88: 'Felicis Ventures, Blackbird Ventures (Australia), Sequoia Capital, Bond\\xa0, General Catalyst',\n",
       "  89: '光际资本、IDG',\n",
       "  90: 'Breyer Capital, IDG Capital, Bitmain, Goldman Sachs Principal Strategic Investments',\n",
       "  91: '顺为资本、元禾原点、前海兴旺',\n",
       "  92: 'Benchmark, Index Ventures, Sequoia Capital',\n",
       "  93: '阿里影业',\n",
       "  94: 'Andreessen Horowitz, New Enterprise Associates',\n",
       "  95: '红杉资本、腾讯、南山资本',\n",
       "  96: 'TPG、凯雷投资，泰康集团、农银国际',\n",
       "  97: 'Founders Fund, DST Global, SF Express, SoftBank Investment Advisers',\n",
       "  98: 'Silver Lake Partners',\n",
       "  99: '纪源资本、磐谷创投、愉悦资本、蚂蚁金服',\n",
       "  100: '华盖资本',\n",
       "  101: '海纳亚洲、Sierra Ventures、前海兴旺',\n",
       "  102: '真格基金、红杉资本、高瓴资本、创新工场、晨兴资本',\n",
       "  103: '毅达资本、紫金资本、顺为资本',\n",
       "  104: 'SoftBank Investment Advisers, Greenoaks Capital',\n",
       "  105: '红杉资本',\n",
       "  106: '光信资本、腾讯、浙商创投、启明创投',\n",
       "  107: 'Y Combinator, Passion Capital, Thrive Capital, Goodwater Capital, Accel, General Catalyst',\n",
       "  108: 'Earlybird Venture Capital, Valar Ventures, Horizons Ventures, Allianz X, Insight Partners, Tencent Holdings',\n",
       "  109: 'Softbank Investment Advisors, Gaorong Capital, Greylock Partners.',\n",
       "  110: 'EDBI, SoftBank Investment Advisers, NIBC Bank N.V., Indiabulls Housing Finance Limited',\n",
       "  111: 'SoftBank, Qualcomm Ventures, Virgin Group',\n",
       "  112: 'Thrive Capital, Founders Fund, Formation 8, CapitalG, Fidelity, Alphabet',\n",
       "  113: 'SoftBank, Alibaba Group',\n",
       "  114: 'Spark Capital, New Enterprise Associates, Goldman Sachs Investment Partners, Index Ventures, Kleiner Perkins',\n",
       "  115: 'Greater Pacific Capital, Bessemer Venture Partners, ICONIQ Capital, Dragoneer Investment Group, Tiger Global Management',\n",
       "  116: 'IDG资本、中信建投资本、华兴创投',\n",
       "  117: 'Y Combinator, Tencent Holdings',\n",
       "  118: 'Index Ventures, Greylock Partners\\xa0, Meritech Capital Partners, Tiger Global Management, Altos Ventures\\xa0, First Round Capital',\n",
       "  119: 'Lightspeed Venture Partners, Greylock Partners, Khosla Ventures, IVP (Institutional Venture Partners), Bain Capital Ventures',\n",
       "  120: '光信资本、奇虎360',\n",
       "  121: 'Clayton, Dubilier & Rice',\n",
       "  122: '晨兴资本、红杉资本、阿里巴巴、华平投资',\n",
       "  123: 'DST Global, Naspers, Bessemer Venture Partners, Accel, Norwest Venture Partners, SAIF Partners',\n",
       "  124: 'New Enterprise Associates, T. Rowe Price, Baillie Gifford, Revolution',\n",
       "  125: 'Bessemer Venture Partners, Generation Investment Management, T. Rowe Price, TCV, Lead Edge Capital, Tiger Global Management',\n",
       "  126: 'Sequoia Capital, WetSummit Capital, DFJ Growth, Silver Lake Partners, Altimeter Capital',\n",
       "  127: '真格基金、红杉资本、创新工场',\n",
       "  128: '创新工场、云锋基金、红杉资本、真格基金、腾讯、经纬中国',\n",
       "  129: 'Bon Angels Venture Partners, Altos Ventures, Goldman Sachs, Hillhouse Capital Group',\n",
       "  130: '红杉资本、腾讯、真格基金、纪源资本、阿里巴巴',\n",
       "  131: '阿里巴巴、高盛',\n",
       "  132: '新浪、红点创投、红杉资本、晨兴资本',\n",
       "  133: '前海梧桐、中创海洋',\n",
       "  134: 'IDG、经纬中国、腾讯、华平投资',\n",
       "  135: 'DFJ, Lux Capital, Blackbird Ventures (Australia), Thomas Tull, Grok Ventures',\n",
       "  136: '纪源资本、H Capital、红杉资本',\n",
       "  137: 'Google, Johnson & Johnson Development Corporation, National Institutes of Health, Sequoia Capital, GlaxoSmithKline',\n",
       "  138: 'Daniel Klueger, Global Asset Management',\n",
       "  139: '京东、凯辉基金、达晨创投、天图资本、晨兴资本',\n",
       "  140: 'Orient Hontai Capital, Kohlberg Kravis Roberts',\n",
       "  141: '海纳亚洲、启明创投',\n",
       "  142: 'Founders Fund, Y Combinator, Generation Investment Management',\n",
       "  143: 'Greylock Partners, Sequoia Capital, Hyundai Motor Company, Index Ventures',\n",
       "  144: 'General Atlantic, Kohler Kravis Roberts, Tiger Global Management, Jefferies',\n",
       "  145: 'Woodford Investment Management',\n",
       "  146: 'Visa, General Atlantic, TA Associates, Clearstone Venture Partners , SBI',\n",
       "  147: 'Vertex Ventures, Black Hole Capital, Funcity Capital',\n",
       "  148: 'Goldcrest Capital, Craft Ventures, Index Ventures, Valor Equity Partners, Sequoia Capital',\n",
       "  149: 'Accel, Index Ventures, Insight Partners, Baring Vostok Capital Partners, SNCF',\n",
       "  150: 'Peter Thiel',\n",
       "  151: 'New Enterprise Associates, Andreessen Horowitz, NBCUniversal, Hearst Ventures, RRE Ventures',\n",
       "  152: '一汽集团、启迪控股、宁德时代',\n",
       "  153: '国投创业、阿里巴巴、联想创投',\n",
       "  154: '阿里巴巴、腾讯、华人文化',\n",
       "  155: 'Sequoia Capital, BMW i Ventures\\xa0, GV, GE Ventures, Baillie Gifford, Madrone Capital Partners',\n",
       "  156: 'Union Square Ventures, Spark Capital, Menlo Ventures,\\xa0Social Capital, Meritech Capital Partners\\xa0, Tribe Capital',\n",
       "  157: 'DST Global\\xa0, Insight Partners',\n",
       "  158: '利欧股份、源码资本、明势资本',\n",
       "  159: 'Crosslink Capital, Aspect Ventures, Cathay Innovation, Menlo Ventures, DST Global,',\n",
       "  160: 'DH Capital, Dievini Hopp Biotech Holding, OH Beteiligungen, Bill & Melinda Gates Foundation, Baillie Gifford, Baden-Württembergische Versorgungsanstalt für Ärzte',\n",
       "  161: 'Invoke Capital Partners, Summit Partners, Kohlberg Kravis Roberts, Talis Capital, Vitruvian Partners',\n",
       "  162: 'IVP (Institutional Venture Partners), Venrock, Fidelity',\n",
       "  163: 'Nexus Venture Partners, Multiples Alternate Asset Management Private Limited,Tiger Global Management, The Carlyle Group, Fosun Group, Softbank, Canada Pension Plan Investment Board',\n",
       "  164: 'Bridgepoint, Fidelity Management and Research Company\\xa0, Amazon, DST Global, General Catalyst, T. Rowe Price, Greenoaks Capital',\n",
       "  165: 'GE Ventures, GV, New Enterprise Associates, Ford Motor Company, Koch Industries, Saudi Aramco Energy Ventures',\n",
       "  166: 'Andreessen Horowitz',\n",
       "  167: 'Andreessen Horowitz, Polychain',\n",
       "  168: 'Benchmark, 9+ Program, Greylock Partners, Index Ventures, Tencent Holdings, Greenoaks Capital, Index Ventures, Accel',\n",
       "  169: 'Permira, TCV, Silver Lake Partners',\n",
       "  170: 'Tiger Global Management, Sequoia Capital India, Accel',\n",
       "  171: 'Kreos Capital, Vostok New Ventures, MCI Capital SA, Volkswagen Group, Sberbank, Dave Waiser, Access Industries',\n",
       "  172: 'Amadeus Capital Partners, Atomico, Sequoia Capital, BMW i Ventures, Robert Bosch Venture Capital\\xa0, Microsoft, Samsung Strategy and Innovation Center',\n",
       "  173: 'General Catalyst,\\xa0Kleiner Perkins, Emergence\\xa0, GV, Ribbit Capital, Akkadian Ventures, Dragoneer Investment Group, T. Rowe Price, Y Combinator',\n",
       "  174: 'Mayfield Fund, GGV Capital, IVP (Institutional Venture Partners), Redpoint',\n",
       "  175: 'Capricorn Investment Group, Panorama Point Partners',\n",
       "  176: 'UBS,Temasek Holdings, Sailing Capital, Horizons Ventures',\n",
       "  177: 'SoftBank Investment Advisers, NetEase, Amadeus Capital Partners, Andreessen Horowitz, Horizons Ventures',\n",
       "  178: 'TPG Growth, Goldman Sachs',\n",
       "  179: 'Polaris Partners, US Venture Partners, Sales Force Ventures',\n",
       "  180: 'FirstMark, Tiger Global Management, Accel, ICONIQ Capital, Battery Ventures, Spark Capital',\n",
       "  181: '中国人寿、IDG、中金资本',\n",
       "  182: 'TPG, Ireland Strategic Investment Fund, Insight partners',\n",
       "  183: 'IDG、金山软件、小米',\n",
       "  184: 'Skion, GmBH, Altana',\n",
       "  185: 'Allianz, SoftBank, Aleph\\xa0, Sequoia Capital Israel',\n",
       "  186: 'Andreessen Horowitz, Coatue Management, Fifth Wall, Bain Capital Ventures, Rainbow Technologies',\n",
       "  187: '今日资本、启明创投、高瓴资本',\n",
       "  188: '83North, Commerce Ventures, IA Capital Group, Visa, ICONIQ Capital, Granite Ventures, Coatue Management',\n",
       "  189: '腾讯、高瓴资本',\n",
       "  190: 'Entrée Capital,\\xa0Genesis Partners, Insight Partners, Stripes Group, Sapphire Ventures',\n",
       "  191: 'Tiger Mangement Corporation, Wellington Management',\n",
       "  192: 'Sequoia Capital India, General Atlantic, MasterCard',\n",
       "  193: 'NANT Health',\n",
       "  194: 'Benchmark, Shasta Ventures, Kleiner Perkins, Insight Partners, Tiger Global Management, Redpoint, Riverwood Capital',\n",
       "  195: 'Morgan Stanley, Brookside Capital',\n",
       "  196: 'Volkswagen Group, Goldman Sachs, Seimens',\n",
       "  197: 'Amgen, IP Group Plc, Woodford Investment Management, Illumina, GT Healthcare Capital Partners',\n",
       "  198: 'Sand Hill Angels, Tao Capital Partners, Tiger Global Management',\n",
       "  199: '广发信德、清华控股、Fidelity',\n",
       "  200: 'Legend Capital, ClearVue Partners\\xa0, Kunlun, Morningside Venture Capital, Eight Roads Ventures',\n",
       "  201: 'Founders Fund, Spark Capital, Harmony Partners, Tiger Global Management, BlackRock, Glynn Capital Management',\n",
       "  202: 'Toyota Motor Corporation',\n",
       "  203: 'Motus Ventures, Rising Tide',\n",
       "  204: 'Benchmark, Adam D’Angelo\\xa0, Tiger Global Management, Collaborative Fund\\xa0, Peter Thiel, Y Combinator',\n",
       "  205: 'IDG、源码资本、红杉资本',\n",
       "  206: 'Goldman Sachs, Abu Dhabi Investment Authority, Asian Development Bank, JERA, Yes Bank, Canada Pension Plan Investment Board, OPIC - Overseas Private Investment Corporation, Abu Dhabi Investment Authority',\n",
       "  207: 'Mastercard Start Path, Balderton Capital, TriplePoint Capital, Index Ventures, DST Global',\n",
       "  208: 'Accel, Thrive Capital, GV, Meritech Capital Partners, Y Combinator',\n",
       "  209: 'Bessemer Venture Partners, ICONIQ Capital, Battery Ventures, Index Ventures',\n",
       "  210: 'Wells Fargo Capital Finance, Wellington Management, Heritage Group, Galen Partners',\n",
       "  211: 'Battery Ventures, ICONIQ Capital, Temasek Holdings, Intel Capital',\n",
       "  212: 'Accel, General Atlantic, Index Ventures',\n",
       "  213: 'PCCW, Hony Capital, Tencent Holdings, TPG Growth',\n",
       "  214: '高盛',\n",
       "  215: '蚂蚁金服、鼎晖投资、新浪',\n",
       "  216: 'Caterpillar Ventures, GreatPoint Ventures, Revolution, Baillie Gifford',\n",
       "  217: 'Tiger Global Management, General Catalyst, T. Rowe Price',\n",
       "  218: '云锋基金、红杉资本、真格基金、高瓴资本',\n",
       "  219: 'TPG, Fidelity, Andreessen Horowitz',\n",
       "  220: '创新工场、今日资本、启明创投、腾讯',\n",
       "  221: 'Atomico, Baillie Gifford, Khosla Ventures, Founders Fund',\n",
       "  222: 'SignalFire, AME Cloud Ventures, SoftBank Investment Advisers',\n",
       "  223: '腾讯、沙钢集团、明驰基金',\n",
       "  224: '未透露',\n",
       "  225: '老虎基金、蚂蚁金服、优客工场',\n",
       "  226: '未透露',\n",
       "  227: '未透露',\n",
       "  228: '万达、经纬中国、海纳亚洲',\n",
       "  229: '前程无忧',\n",
       "  230: '华谊兄弟、红杉资本、真格基金',\n",
       "  231: '西部优势资本、中合担保',\n",
       "  232: '新浪、软银赛富、摩根士丹利',\n",
       "  233: '红杉资本、达晨创投 、华兴新经济基金、易方达基金',\n",
       "  234: 'CPEChina Fund、中金资本、霸菱亚洲',\n",
       "  235: '昆仑信托',\n",
       "  236: '华平投资、景林投资、高瓴资本',\n",
       "  237: '红杉资本、经纬中国、高盛',\n",
       "  238: '红杉资本、鼎晖投资',\n",
       "  239: '百度、红杉资本、真格基金',\n",
       "  240: '中航信托、华平投资、德同资本',\n",
       "  241: '商汤科技、软银中国、曜为资本',\n",
       "  242: 'SMG',\n",
       "  243: '红杉资本、小米、顺为资本',\n",
       "  244: '赛伯乐、韩亚金融集团、建信信托',\n",
       "  245: '红杉资本',\n",
       "  246: '阿里巴巴、高盛、中投',\n",
       "  247: 'JAFC、IDG、景林资本、红杉资本',\n",
       "  248: '红杉资本、君联资本、高瓴资本',\n",
       "  249: '恒泰华盛、百石基金',\n",
       "  250: '贝恩资本',\n",
       "  251: 'IDG、华创资本、启明创投、纪源资本',\n",
       "  252: '红杉资本、经纬中国、58同城',\n",
       "  253: '高瓴资本、启明创投、君联资本、红杉资本',\n",
       "  254: '携程、纪源资本、启明创投、鼎晖投资',\n",
       "  255: '宽带资本、中金公司',\n",
       "  256: '腾讯、华平投资、经纬中国',\n",
       "  257: '腾讯、华人文化产业基金',\n",
       "  258: '淡马锡、红杉资本、云锋基金、',\n",
       "  259: '愉悦资本、贝塔斯曼、君联资本、晨兴资本',\n",
       "  260: '百度、闻名投资',\n",
       "  261: '赛伯乐、IDG',\n",
       "  262: 'IDG、经纬中国、红杉资本、真格基金',\n",
       "  263: '中国国新、中金前海、红杉资本、IDG、高瓴资本',\n",
       "  264: 'Foresite Capital, Fidelity Management and Research Company, Meritech Capital Partners, Silicon Valley Bank',\n",
       "  265: '真格基金、顺为资本、老虎基金',\n",
       "  266: '阿里巴巴、天弘基金、中信证券',\n",
       "  267: '红杉资本、国新、启迪、创新工场',\n",
       "  268: '晨兴资本、DCM、SIG',\n",
       "  269: 'SevenVentures, Bestseller',\n",
       "  270: 'Greylock Partners\\xa0, North Bridge Venture Partners & Growth Equity, Advanced Technology Ventures, Andreessen Horowitz, TCV. Crestline, Tiger Global Management',\n",
       "  271: 'ICONIQ Capital',\n",
       "  272: 'CRV, Caffeinated Capital, Benchmark\\xa0, Coatue Management, Thrive Capital',\n",
       "  273: '腾讯、红杉资本、DST、高瓴资本',\n",
       "  274: '启明创投、蚂蚁金服',\n",
       "  275: '云峰基金、太平资产',\n",
       "  276: 'Lerer Hippeau, Maveron, Tiger Global Management, T. Rowe Price',\n",
       "  277: 'Sailing Capital, Longitude Capital',\n",
       "  278: '红杉资本、凯雷投资、高盛、华平投资',\n",
       "  279: '软银中国、大中投资',\n",
       "  280: 'Inovia Capital, Mithril Capital Management, JP Morgan Chase',\n",
       "  281: 'Bessemer Venture Partners, Trinity Ventures, Meritech Capital Partners, Sapphire Ventures',\n",
       "  282: 'Inside Partners, Tiger Global Management, Polaris Partners',\n",
       "  283: 'Bain Capital Ventures, Fifth Third Capital, Caisse, Charlotte Angel Partners, CT Communications, Mastercard',\n",
       "  284: 'Global Founders Capital, Wellington Management, Accel, Forerunner Ventures',\n",
       "  285: '国投创新、云锋基金、尚颀资本',\n",
       "  286: 'IDG、北极光创投、今日资本',\n",
       "  287: 'Mirae Asset-Naver Asia Growth Fund, Alibaba Group, Helion Venture Partners, Abraaj Group, Bessemer Venture Partners, LionRock Capital, Brand Capital, Ascent Capital',\n",
       "  288: 'Franklin Templeton Investments, DCM Ventures, Emergence, Financial Partners Fund, Scale Venture Partners, Bank of America, Silicon Valley Bank, JP Morgan, Temasek Holdings',\n",
       "  289: 'Bill Tai, EY Startup Challenge, Credit China FinTech Holdings, Korelya Capital',\n",
       "  290: 'Didi Chuxing, Daimler',\n",
       "  291: '高盛、集富亚洲、点亮资本',\n",
       "  292: '盛世投资、中科产业基金',\n",
       "  293: 'New Enterprise Associates, TripplePoint Capital, Zach Coelius',\n",
       "  294: 'Mirae Asset-Naver Asia Growth Fund, Emtek Group',\n",
       "  295: 'Fidelity',\n",
       "  296: 'TPG Growth, Breyer Capital',\n",
       "  297: 'Kevin Laws, Seaya Ventures, Rakuten Capital, Inter American Development Bank',\n",
       "  298: 'TPG Growth, Insight Partners',\n",
       "  299: '基石资本、华平投资、阿里巴巴',\n",
       "  300: 'Lerer Hippeau, New Enterprise Associates, IVP (Institutional Venture Partners), Target',\n",
       "  301: '83North, Accel',\n",
       "  302: 'Quantum Energy Partners, Seimens, Daimler, Linse Capital',\n",
       "  303: '浙富控股、元璟资本',\n",
       "  304: '九鼎资本、毅达资本',\n",
       "  305: '蓝驰创投、贝塔斯曼、中金公司',\n",
       "  306: 'Franklin Templeton Investments, Summer@Highland, Pelion Venture Partners\\xa0, New Enterprise Associates, Union Square Ventures, Venrock, Fidelity',\n",
       "  307: 'First Round Capital, Sequoia Capital, Greenoaks Capital',\n",
       "  308: 'SoftBank Investment Advisers, Sequoia Capital\\xa0, Artis Ventures (AV), GV, Wing Venture Capital, Qualcomm Ventures',\n",
       "  309: 'Newion Investments, Index Ventures, ICONIQ Capital, Battery Ventures, Capital G',\n",
       "  310: 'JP Morgan partners, Benchmark',\n",
       "  311: 'Greylock Partners, Y Combinator, CapitalG',\n",
       "  312: 'GSV Asset Management, SEEK Group, Kleiner Perkins\\xa0, New Enterprise Associates, THE WORLD BANK GROUP, New Enterprise Associates, EDBI',\n",
       "  313: '老虎基金、华平资本、好未来',\n",
       "  314: '阿里巴巴、KKR、平安创投',\n",
       "  315: 'New Enterprise Associates, Meritech Capital Partners,Sapphire Ventures',\n",
       "  316: 'Sky, Thomveste Ventures, Atlas Venture, Flybridge Capital Partners',\n",
       "  317: 'Access Industries, Idinvest Partners, Kingdom Holding Company,Orange',\n",
       "  318: '老虎环球基金、北极光创投、GIC',\n",
       "  319: 'Greylock Partners, Sequoia Capital, Insight Partners',\n",
       "  320: 'Kerala Ventures, Accel, Bpifrance, Eurazeo, General Atlantic, AGORANOV',\n",
       "  321: '高榕资本、光速中国、晨兴资本',\n",
       "  322: '21st Century Fox, Revolution, Eldridge Industries, The Raine Group, Redpoint',\n",
       "  323: 'Tencent Holdings, Steadview Capital',\n",
       "  324: 'Viking Global Investors, Riverwood Capital, Sequoia Capital India, Nexus Venture Partners, Indian Angel Network',\n",
       "  325: '阿里巴巴、银杏谷资本',\n",
       "  326: '顺为资本、DCM、腾讯',\n",
       "  327: '海航旅游、H-capital',\n",
       "  328: '红杉资本',\n",
       "  329: 'M8 Capital, Sequoia Capital, DoCoMo Capital, Meritech Capital partners',\n",
       "  330: 'Insight Partners, ICONIQ Capital, Wellington Management, Lightspeed Venture Partners, GIC',\n",
       "  331: 'Sherpa Capital, Softbank Investment Advisors, Javelin Venture partners, Silicon Valley Bank, Next47',\n",
       "  332: '嘉御基金、光速中国、鼎晖投资',\n",
       "  333: '海纳亚洲、启明创投、乐天',\n",
       "  334: '顺丰速运、鼎晖投资、国开金融',\n",
       "  335: 'DFJ Growth, Foundry Group, Tyche Partners, New Enterprise Associates, SOSV',\n",
       "  336: 'DCM、北极光创投、IDG、高瓴资本',\n",
       "  337: '厚朴投资、经纬中国、腾讯',\n",
       "  338: '金沙江创投、新浪、亚信联创',\n",
       "  339: 'PROfounders Capital, Highland Europe\\xa0, Fritz Demopoulos, Spark Capital, Kohlberg Kravis Roberts, Battery Ventures, Swisscanto Invest, SoftBank Investment Advisers, Kees Koolen',\n",
       "  340: 'Viking Global Investors',\n",
       "  341: 'Goldman Sachs Principal Strategic Investments, Khosla Ventures, August Capital, GV, ICONIQ Capital',\n",
       "  342: 'Lewis trust Group. Rocket Internet, Kinnevik AB',\n",
       "  343: 'Thrive Capital, IVP (Institutional Venture Partners), Index Ventures, Sequoia Capital',\n",
       "  344: 'Softbank Investment Advisors, General Atlantic',\n",
       "  345: '挚信资本、崇德投资、DCM中国',\n",
       "  346: 'Norwest Venture Partners, Kaiser Permanente Ventures, Sorenson Capital, UPMC,OrbiMed',\n",
       "  347: 'Foxconn Technology Group, Tencent Holdings, Bharti SoftBank, Tiger Global Management',\n",
       "  348: 'Atomic, Thrive Capital, IVP (Institutional Venture Partners)',\n",
       "  349: 'Ginko Ventures',\n",
       "  350: '德同资本、方正和生、富坤投资',\n",
       "  351: '知合出行、鸿利智汇',\n",
       "  352: '海纳亚洲、Intel Capital、海通开元',\n",
       "  353: '泛海控股、复星锐正资本',\n",
       "  354: '汉能投资、软银、顺为资本、海纳亚洲',\n",
       "  355: 'Illumina Ventures',\n",
       "  356: '天府集团、鑫根资本',\n",
       "  357: 'Greycroft, Premji Invest',\n",
       "  358: 'Just Eat, Movile, Warehouse Investimentos, Naspers',\n",
       "  359: '天图资本、达晨创投、正和岛基金',\n",
       "  360: 'J.P. Morgan Asset Management, Andreessen Horowitz, General Catalyst, Accel, BlackRock',\n",
       "  361: 'Softbank Capital, Kleiner Perkins, Sherpalo Ventures',\n",
       "  362: 'Social Capital, Bessemer Venture Partners, ICONIQ Capital, Index Ventures, Kleiner Perkins',\n",
       "  363: '腾讯领投，今日资本',\n",
       "  364: 'Saban Capital Group, Access Industries',\n",
       "  365: '启明创投、GIC、高盛',\n",
       "  366: 'Ardian, Kohlberg Kravis Roberts, Tiger Global Management',\n",
       "  367: 'Insight Partners, Vmware',\n",
       "  368: '红杉资本、东方富海',\n",
       "  369: '红杉资本、君联资本、鼎晖投资',\n",
       "  370: '天图资本、招银国际、浙江金控',\n",
       "  371: '普洛斯、新希望、远洋资本',\n",
       "  372: 'IDG资本、信中利资本、键桥通讯',\n",
       "  373: 'BlueRun Ventures, Mohr Davidow Ventures, Thomvest Ventures, Guggenheim Securities, SoftBank Capital, Reverence Capital Partners, Credit Suisse',\n",
       "  374: 'Index Ventures, Scale Venture Partners, IVP (Institutional Venture Partners), Greenoaks Capital',\n",
       "  375: 'Berkshire Partners, Norwest Venture Partners',\n",
       "  376: 'Kohlberg Kravis Roberts, Goldman Sachs, Elephant',\n",
       "  377: '阿里巴巴、联想之星、好未来教育集团',\n",
       "  378: 'IDG、歌斐资产',\n",
       "  379: '清流资本、襄禾资本、顺为资本',\n",
       "  380: '经纬中国、晨兴资本',\n",
       "  381: '红杉资本、上海电气、兴业证券',\n",
       "  382: 'Naspers',\n",
       "  383: '红杉资本、光大实业、赛伯乐',\n",
       "  384: 'Viola Ventures, Insight Partners, Goldman Sachs Private Capital Investing, ClalTech',\n",
       "  385: '中投公司',\n",
       "  386: '腾讯、泛海投资、中信资本',\n",
       "  387: '腾讯、弘毅投资',\n",
       "  388: 'IDG Capital',\n",
       "  389: 'SoftBank Investment Advisers, SoftBank, DOMO Invest\\xa0, Monashees\\xa0, Dragoneer Investment Group, IFC Venture Capital Group\\xa0, Iporanga Investments, Qualcomm Ventures, Microsoft',\n",
       "  390: 'IDG、真格基金',\n",
       "  391: 'T. Rowe Price, Andreessen Horowitz, Deutsche Telekom, Intex Ventures, Khosla Ventures',\n",
       "  392: '顺为资本、启明创投、真格基金、红杉资本、腾讯',\n",
       "  393: 'DST、IDG、晨兴资本、DCM',\n",
       "  394: 'Sequoia Capita, Lehman Brothers, Tenaya Capital, Wellington Management, NTT Data',\n",
       "  395: 'Silicon Valley Bank, Goldman Sachs, Searchlight Capital Partners',\n",
       "  396: 'Avenir Growth Capital, Eurazeo Prime Ventures',\n",
       "  397: 'Koch Disruptive Technologies, T. Rowe Price, Hewlett Packard Enterprise, Khosla ventures, Andreessen Horowitz',\n",
       "  398: '红杉资本、启明创投',\n",
       "  399: 'CITIC Securities',\n",
       "  400: 'Hinduja Group, Leonardo DiCaprio, Venture Kick',\n",
       "  401: '红杉资本、分享投资',\n",
       "  402: '真格基金、红杉资本、海纳亚洲',\n",
       "  403: '创新工场、腾讯、真格基金、顺为资本、纪源资本',\n",
       "  404: 'Edison Partners,Greenspring Associates',\n",
       "  405: 'Social Capital, Lightspeed Venture Partners, Accel, ICONIQ Capital',\n",
       "  406: '-',\n",
       "  407: '红杉资本、华兴资本、天图资本、今日资本',\n",
       "  408: '招银国际、国投创新',\n",
       "  409: 'T. Rowe Price, Warburg Pincus, Jackson Square Ventures',\n",
       "  410: 'Matrix Partners India, Tata Sons Ltd, SoftBank, Tiger Global Management',\n",
       "  411: 'Goldman Sachs Investment Partners, Kleiner Perkins, Kinnevik AB, Silver Lake Kraftwerk, Temasek Holdings, Battery Ventures, Lakestar, New Enterprise Associates, Hasso Plattner Ventures',\n",
       "  412: 'The Carlyle Group, Benchmark, GV, Redmile Group, J.P. Morgan Asset Management, Maverick Ventures, Oak Investment Partners',\n",
       "  413: 'Insight Partners',\n",
       "  414: '蚂蚁金服、赛富投资、松禾资本',\n",
       "  415: 'Clal Insurance Enterprises Holdings\\xa0, Meitav Investment House, Intel Capital',\n",
       "  416: 'Mayfield Fund, Trinity Ventures, DFJ Growth, Spark Capital, Lone Pine Capital',\n",
       "  417: 'Armilar Venture Partners, North Bridge Venture Partners & Growth Equity, Goldman Sachs, Kohlberg Kravis Roberts',\n",
       "  418: 'Mitsubishi Corp',\n",
       "  419: 'Softbank Investment Advisors',\n",
       "  420: 'ONE Luxury Group, Eurazeo',\n",
       "  421: 'DST、虎扑体育、普思资本',\n",
       "  422: 'SoftBank Investment Advisors, Wellington Management, Premji Invest, Tiger Global Management, Inventus Capital Partners',\n",
       "  423: '丹丰资本、软银中国资本',\n",
       "  424: 'Yuan Capital, Harbin Gloria Pharmaceuticals, Lycos Ventures',\n",
       "  425: 'Trifecta Capital Advisors, Tiger Global Management, InnoVen Capital, Brand Capital, Kinnevik AB, Warburg Pincus, NGP Capital, Norwest Venture Partners, Omidyar Network',\n",
       "  426: 'Accel, New Enterprise Associates',\n",
       "  427: 'SoftBank, SoftBank Investment Advisers, Y Combinator, Andreessen Horowitz, Sequoia Capital, Delivery Hero, DST Global',\n",
       "  428: '高盛、腾讯、滴滴、顺为资本',\n",
       "  429: '挚信资本',\n",
       "  430: 'Bain Capital Ventures, Highland Capital Partners, Kleiner Perkins, American Express Ventures, TCV, Fidelity Management and Research Company, Novel TMT Ventures, Blue Pool Capital, Temasek Holdings, Franklin Templeton Investments',\n",
       "  431: '500 Startups, K2 Global',\n",
       "  432: 'SAIF Partners, Warburg Pincus',\n",
       "  433: 'Bessemer Venture Partners, Data Collective DCVC, Future Fund',\n",
       "  434: 'Drive Capital, Ribbit Capital, Redpoint, Tiger Global Management',\n",
       "  435: 'QuarterMoore, Rotunda Capital Partners, Fifth Third Bancorp, Nima Capital, SUEZ Environnement, Promecap, NZ Super Fund',\n",
       "  436: 'Jackson Square Ventures, JMI Equity, General Atlantic, Lightspeed Venture Partners\\xa0, T. Rowe Price,',\n",
       "  437: 'GIC, Tiger Global Management, Nexus Venture Partners, Helion Venture Partners',\n",
       "  438: '百度、蔚来资本',\n",
       "  439: '腾讯、创新工场、IDG、美团点评',\n",
       "  440: 'Sutter Hill Ventures, Daimler',\n",
       "  441: '启明创投',\n",
       "  442: '顺为资本、GIC、纪源资本',\n",
       "  443: 'Tao Capital Partners, Valor Equity Partners',\n",
       "  444: 'Nvidia GPU Ventures, Tencent Holdings, Walden Venture Capital',\n",
       "  445: 'DST Global, General Atlantic, GGV Capital, Battey Ventures',\n",
       "  446: 'Greylock Partners, Accel, Sequoia Capital, DFJ Growth, Sapphire Ventures, Battery Ventures',\n",
       "  447: 'Fidelity, Revolution, T. Rowe Price',\n",
       "  448: 'Mitsubishi UFJ Financial Group, Standard Chartered Bank, BNP Paribas Private Equity',\n",
       "  449: 'Fidelity Management and Research Company, Pitango Venture Capital, Marker, Evergreen Venture Partners',\n",
       "  450: 'Viking Global Investors, Storm Ventures, DFJ, Salesforce Ventures',\n",
       "  451: '软银中国、麦顿投资、北极光创投',\n",
       "  452: 'Alibaba Group, DFJ',\n",
       "  453: 'Matrix Partners, Rho Capital Partners, Shining Capital',\n",
       "  454: '腾讯、碧桂园创投、红杉资本',\n",
       "  455: 'General Catalyst, Institutional Venture Partners, Wellington Management, L Catterton, Glade Brook Capital Partners',\n",
       "  456: 'Lightspeed Venture Partners, Sapphire Ventures, Khosla Ventures, General Catalysts',\n",
       "  457: 'CapitalG, Baillie Gifford, Javelin Venture Partners, Sequoia Capital',\n",
       "  458: 'Simone Investment Managers, NHM Invesment Corp, Kohlberg Kravis Roberts, Anchor Equity Partners',\n",
       "  459: 'Altos Ventures, Goodwater Capital, GIC, Kleiner Perkins, Sequoia Capital China, Ribbit Capital',\n",
       "  460: 'PayPal, Notion, Kite Ventures, Scentan Ventures, Data Collective DCVC, Wipro Ventures, Goldman Sachs Principal Strategic Investments\\xa0, RTP Global, PSP Investments',\n",
       "  461: 'GCP Capital Partners',\n",
       "  462: 'Kleiner Perkins, SK Holdings, August Capital, IAC',\n",
       "  463: 'Sina, Composite Capital Management',\n",
       "  464: 'DCM、贝塔斯曼、君联资本',\n",
       "  465: 'Lightspeed Venture Partners, DST Global',\n",
       "  466: 'Bertelsmann, Andreessen Horowitz, CRV',\n",
       "  467: '启明创投、高通',\n",
       "  468: '华平投资',\n",
       "  469: 'Softbank Investment Advisors, Blackrock, TIAA, Madrone Capital Partners, NanoDimension',\n",
       "  470: 'Salesforce Ventures, Sutter Hill Ventures',\n",
       "  471: 'NBC Universal, General Atlantic, Accel, Khosla Ventures',\n",
       "  472: 'Bessemer Venture Partners, Thrive Capital, OpenView Venture Partners, Insight Partners, Brookfield Asset Management',\n",
       "  473: '新天域资本、光信资本、IDG、启明创投',\n",
       "  474: 'Gemini Israel Ventures, Scale Venture Partners, Greenspring Associates, Insight Partners, EDBI',\n",
       "  475: 'TOM集团、Khazanah、IFC、红杉资本',\n",
       "  476: '海通开元、北极光创投',\n",
       "  477: 'IDG、赛富基金、百度',\n",
       "  478: '粤民投、厚朴投资、胡润百富',\n",
       "  479: 'Partners Investment, Sky Lake Investment, Booking Holdings, GIC',\n",
       "  480: '众信旅游、红杉资本、创新工场',\n",
       "  481: '涌铧投资、汇能金融、磐石资本',\n",
       "  482: '凤凰、小米、IDG',\n",
       "  483: '美团点评、腾讯、贝塔斯曼',\n",
       "  484: '博裕资本、厚朴投资、普洛斯、源码资本、鼎晖投资',\n",
       "  485: '远镜创投、赛富基金',\n",
       "  486: '高瓴资本、晨兴资本、软银中国',\n",
       "  487: '君联资本、慕华投资',\n",
       "  488: '华平投资、红杉资本、经纬中国',\n",
       "  489: 'GPI Capital, GSO Capital Partners',\n",
       "  490: '顺为资本、达晨创投、华平投资',\n",
       "  491: '腾讯',\n",
       "  492: 'Sequoia Capital, Visionnaire Ventures, Katalyst.Ventures',\n",
       "  493: 'IVP (Institutional Venture Partners)'}}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.to_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 练习B1_post-读读读的课堂后练习\n",
    "\n",
    "老手有彩蛋项目可实践\n",
    "\n",
    "IMF有[2020年1月的《世界经济展望》](https://www.imf.org/zh/Publications/WEO/Issues/2020/01/20/weo-update-january2020)，而这数据集的前一份版本都可以在其[数据入口取得](https://www.imf.org/en/data)的EXCEL数据可以下载，共用三种形式，你能用正确的参数取得数据框吗? \n",
    "* “SDMX Data” [全数据](https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/download.aspx) [zip](https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/WEOOct2019_SDMXData.zip)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# B1 bonus\n",
    " \n",
    "# 你的代码\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![02_io_readwrite.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/02_io_readwrite.svg)\n",
    "### 读读读的小结\n",
    "1. 1 df.info()可以列出这个数据框的所有变数\n",
    "2. 2 读到csv = pd.read_csv(\"路径档案名\", encoding=\"utf8\")\n",
    "3. 3 读到tsv = pd.read_csv(\"路径档案名\", encoding=\"utf8\", sep=\"\\t\")\n",
    "4. 4 读到excel = pd.read_excel(\"路径档案名\", sheet_name=\"分页名称\")\n",
    "\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![03_subset_columns_rows.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/03_subset_columns_rows.svg)\n",
    "## 如何选择表格的子集？  \n",
    "\n",
    "切切切，**切片** (英文叫slice) 是数据科学家找突破点的重要工具，是她们的数据解剖刀...\n",
    "\n",
    "参考 CheatSheet \n",
    "* Subset Observations (Rows) 列\n",
    "* Subset Variables (Columns) 行\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 切切切的代码片语\n",
    "切切切的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "\n",
    "####  列子集\n",
    "```python\n",
    "\n",
    "df.loc()\n",
    "df.iloc()\n",
    "df.set_index()\n",
    "df.head(n)\n",
    "df.tail(n)\n",
    "df.nlargest(n, '变量')\n",
    "df.nsmallest(n, '变量')\n",
    "df[df.估值（亿人民币）> 10]\n",
    "```\n",
    "\n",
    "#### 行子集\n",
    "```python\n",
    "\n",
    "#  行子集\n",
    "df[['变量X','变量Y','变量Z']]\n",
    "df[['变量X']]\n",
    "df['变量X']\n",
    "```\n",
    "\n",
    "#### 列+行子集\n",
    "```python\n",
    "\n",
    "#  行子集\n",
    "df.loc[:,['变量X':'变量Z']]    # 注意中括号里的: 和 ,的使用\n",
    "df.iloc[:,[1,2,5]]\n",
    "df.loc[df['变量X']>10, ['变量X','变量Z'] ]   \n",
    "```\n",
    "\n",
    "子集代码片语说明(你来做笔记)\n",
    "* 列子集\n",
    "* 行子集\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2 entries, 0 to 2\n",
      "Data columns (total 3 columns):\n",
      "排名          2 non-null int64\n",
      "企业名称        2 non-null object\n",
      "估值（亿人民币）    2 non-null int64\n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 64.0+ bytes\n"
     ]
    }
   ],
   "source": [
    "df.loc[[0,2],[\"排名\",\"企业名称\",\"估值（亿人民币）\"]].info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   排名  企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "0   1  蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1   2  字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2   3  滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "\n",
       "                   部分投资机构  \n",
       "0          春华资本、中投海外、红杉资本  \n",
       "1     红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2  腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"估值（亿人民币）\"]> 3500]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![03_subset_columns_rows.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/03_subset_columns_rows.svg)\n",
    "### 切切切的小结\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "1. 1\n",
    "2. 2\n",
    "3. 3\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![04_plot_overview.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/04_plot_overview.svg)\n",
    "## 如何在熊猫中绘图？\n",
    "\n",
    "> <mark>绘绘绘</mark>，**绘图** ( 数据框.plot() ) 是数据科学家**以数据框为中心**的代码实践，减少以图表类型为开头的编程思维来作图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 绘绘绘的代码片语\n",
    "绘绘绘的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "```python\n",
    "df.plot()\n",
    "```\n",
    "\n",
    "代码片语说明\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25aa5b7f708>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[[\"估值（亿人民币）\"]].plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25aa5943e08>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl  \n",
    "mpl.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签  \n",
    "mpl.rcParams['axes.unicode_minus']=False #用来正常显示负号 \n",
    "\n",
    "df.loc[[0,1,2,3,4,5],[\"估值（亿人民币）\"]].plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![04_plot_overview.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/04_plot_overview.svg)\n",
    "### 绘绘绘的小结\n",
    "\n",
    "1. 1\n",
    "2. 2\n",
    "3. 3\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![05_newcolumn_2.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/05_newcolumn_2.svg)\n",
    "## 如何从现有列创建派生新列？\n",
    "> <mark>列列列</mark>，派生新列意谓着变数variables的进一部转换，是数据科学家按步就班做ETL的过程，新派生列就是**变数variables**的转换\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 列列列的代码片语\n",
    "列列列的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "```python\n",
    "\n",
    "df['新变量'] = df['变量X'] + df['变量Y']\n",
    "df['新变量'] = [ 转换(x) for x in df['变量Y'] ]     # 列表推导转换\n",
    "\n",
    "```\n",
    "\n",
    "代码片语说明\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![05_newcolumn_2.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/05_newcolumn_2.svg)\n",
    "### 列列列的小结\n",
    "\n",
    "1. 1\n",
    "2. 2\n",
    "3. 3\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![06_groupby.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/06_groupby.svg)\n",
    "\n",
    "## 如何计算汇总描述性统计信息？\n",
    "算算算，描述性统计竟然代码可以这麽容易....，但难的仍是在数据科学家的数据定义及解释上"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 算算算的代码片语\n",
    "算算算的代码片语 (code snippets)，新手请认真记忆，**注意标点及缩进**\n",
    "\n",
    "```python\n",
    "\n",
    "df.describe()\n",
    "df.describe(include=all)\n",
    "\n",
    "df.count()\n",
    "df.sum()\n",
    "\n",
    "df.min()\n",
    "df.max()\n",
    "df.mean()\n",
    "df.median()\n",
    "\n",
    "df.var()\n",
    "df.std()\n",
    "```\n",
    "\n",
    "代码片语说明\n",
    "\n",
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![06_groupby.svg](https://pandas.pydata.org/pandas-docs/version/1.0.2/_images/06_groupby.svg)\n",
    "### 算算算的小结预告\n",
    "\n",
    "1. 1\n",
    "2. 2\n",
    "3. 3\n",
    "\n",
    "<div class=\"emoticon\">😃😄😁</div>\n",
    "\n",
    "----- \n",
    "----- "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 本周我的总结"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "小结文字说明还没做好，找时间完成"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
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